{"as_of":"2026-08-19T04:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c6a7d8f94e32d853ab61891b9cdc5e7d31ae856e24650824228c249ce17bc56","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T10:05:23.399031Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T10:05:23.079867Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T10:05:23.511684Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"cited_work":{"arxiv_id":"1909.00084","doi":null,"metadata_source":"pith","pith_arxiv_id":"1909.00084","snapshot_observed_at":"2026-08-14T10:05:23.511684Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","venue":"cs.DB","work_id":"84f0e93b-fac4-4c6a-a93a-d46e91aae7d8","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.079867Z"},"links":{"cited_paper":"/paper/1909.00084","citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:057093e902ffccbd39e934618106344f7723cf85cf3f37aed90f2d00b176dc56","observation_id":"aba6d5f1-942d-4d0b-8b65-27c5c436cf62","resolution":{"observed_at":"2026-08-14T10:05:23.517292Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1909.00084/citation-record","integrity":"/paper/1909.00084/integrity","json":"/paper/1909.00084/citation-record.json","paper":"/paper/1909.00084"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"cited_work":{"arxiv_id":"1909.00084","doi":null,"metadata_source":"pith","pith_arxiv_id":"1909.00084","snapshot_observed_at":"2026-08-14T10:05:23.511684Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","venue":"cs.DB","work_id":"84f0e93b-fac4-4c6a-a93a-d46e91aae7d8","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.079867Z"},"links":{"cited_paper":"/paper/1909.00084","citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:057093e902ffccbd39e934618106344f7723cf85cf3f37aed90f2d00b176dc56","observation_id":"aba6d5f1-942d-4d0b-8b65-27c5c436cf62","resolution":{"observed_at":"2026-08-14T10:05:23.517292Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.654393Z","title":"average model accuracy","venue":null,"work_id":"37362861-c539-4994-8181-944af8f3482e","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.087503Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:1db3778745d955b535cbbbcee9218cf7250dc90415a182393d1068b41d9cf404","observation_id":"68ceba4c-4b8f-4c1b-b1c1-a6283cf81988","resolution":{"observed_at":"2026-08-14T10:05:24.660076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.638131Z","title":"An ML model is software derived from data","venue":null,"work_id":"1c1e690c-3cdd-43c1-8c70-c1360e7acbd0","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.093185Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:22c29223f909ccab8b35983668fa49c0a3d055eb966f2579c0db3562f21c13f8","observation_id":"4c23cd7c-4617-4827-ae21-775618b17c42","resolution":{"observed_at":"2026-08-14T10:05:24.643637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.621183Z","title":"We speculate that this relates to the extra challenges introduced by EGML, and believe this area is primed for disruptive research, as we discuss in more details in § 4","venue":null,"work_id":"f8436438-68b5-4c2b-8905-6f2f1842ea51","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.099872Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:33e3c4a0876fb3ffb6c3a1419c9bff3f68072912980baeed7dd54a77a2383bfc","observation_id":"532fcfad-06ef-4760-b1ab-9e52d0751440","resolution":{"observed_at":"2026-08-14T10:05:24.626995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.601576Z","title":"automate it, and don’t get me sued","venue":null,"work_id":"d7a4aa45-8bcb-4aea-bda2-07d8b444633a","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.105154Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:b7c61d2aee638eb76d0314d204009adc7700d61056ca8f6cc70f12be98854d08","observation_id":"3915b478-4e7e-496d-b5c5-3d20702b01a2","resolution":{"observed_at":"2026-08-14T10:05:24.607745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.580355Z","title":"We summarize some key challenges below and present some of our ongoing work","venue":null,"work_id":"eb88fa1b-b9b8-4cf9-9bfc-308b8f99f200","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.111361Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:4934af2dc0b569b0314a3f9901f7c9484d9eade80e608a97c4bd05fdf4c844ef","observation_id":"e2f19457-4267-4d6d-98d9-5f5876b13d49","resolution":{"observed_at":"2026-08-14T10:05:24.588303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.556075Z","title":null,"venue":null,"work_id":"615ef5f0-3785-4f47-a491-52e72d11199f","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.117485Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:43c9001c21722ba497c693f3e7f84d423df622e25615819b60a51e71880dc086","observation_id":"1e993eee-6558-40ab-9891-d47785fff4c0","resolution":{"observed_at":"2026-08-14T10:05:24.563046Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.537137Z","title":"https://calcite.apache.org","venue":null,"work_id":"00416b02-9f90-4150-a48c-118464dcbc32","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.122774Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:8033ae2d68fd51784bd20e5195dcb4be7918a420ade47707c4cdad6c8396c561","observation_id":"73905205-2c03-48cc-9aa8-a238a4492bb4","resolution":{"observed_at":"2026-08-14T10:05:24.543020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.519008Z","title":"https://docs.microsoft.com/en-us/analysis-services/ analysis-services-overview, 2000","venue":null,"work_id":"6ee06368-fb60-4f5d-860b-959dbf3d6ece","year":2000},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.128344Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:acd89fe3af8e6939d0eb67dc48d43d16e96400e04a8dd8ab859b48f6bd00d1ec","observation_id":"8954c8e9-139e-4155-9d9a-edfcaa244df8","resolution":{"observed_at":"2026-08-14T10:05:24.524702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.498494Z","title":"https://mahout.apache.org, 2011","venue":null,"work_id":"b222008b-c30e-4386-8e4b-ef770e5868d1","year":2011},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.133861Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:7605b1eca74758d7fc7f702b2fb0ca59958a40e71ec27a8de0bd355b9ee2169a","observation_id":"e1343454-c790-45b0-b577-201ec6d6bf84","resolution":{"observed_at":"2026-08-14T10:05:24.504301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.470907Z","title":"https://docs.microsoft.com/en-us/sql/advanced-analytics/, 2017","venue":null,"work_id":"ab16dda4-7170-4f60-8169-62042301bf0d","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.139002Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:f938e5891bbd0c34c0df13058447eced018c73a5cb9ac5a143b2ea2095464b39","observation_id":"98296ff5-e70d-43e8-bb53-72f7b34a0c11","resolution":{"observed_at":"2026-08-14T10:05:24.477087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.443166Z","title":"https://www.kaggle.com/paultimothymooney/ 2018-kaggle-machine-learning-data-science-survey, 2018","venue":null,"work_id":"7ca4b3b8-e4eb-4b6f-b561-d413cad41f05","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.143886Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:d4743e8a833e7ea8ebaf1a94c67a8c77483eb14138f29e92473cda6eca0df8c0","observation_id":"f154e1d0-bb25-44d1-a0d1-9d43ced8f9fa","resolution":{"observed_at":"2026-08-14T10:05:24.454901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.423227Z","title":"https: //cloud.google.com/bigquery-ml/docs/bigqueryml-intro, 2018","venue":null,"work_id":"7aa3b627-2fe2-4837-a0c3-0a852ae9e62e","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.149178Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:28cfef7517929df35583c38ec547db61da50726a7cf715b6c4afb428bf1f013a","observation_id":"be84ac04-a47a-4503-9972-ab8839f9f1eb","resolution":{"observed_at":"2026-08-14T10:05:24.429544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.405413Z","title":"https://eng.uber.com/scaling-michelangelo/, 2018","venue":null,"work_id":"7ab0ff54-fb48-4af1-8e18-ad29244c4ed8","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.154205Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:be18c4edeea5928235e424eae636ea0584f659af1a8a4ab9f6382cc836463028","observation_id":"ba18ab43-2386-410a-84f1-4b49d0382bb6","resolution":{"observed_at":"2026-08-14T10:05:24.411166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.388413Z","title":"https://engineering.linkedin.com/blog/2019/01/ scaling-machine-learning-productivity-at-linkedin, 2018","venue":null,"work_id":"084669c4-128c-417e-a598-8e4e428afe43","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.159099Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:c2066e3c3490414952e1f504ba9b1cdac11bfbd8d82caec43ba276df119adc7e","observation_id":"347f3f06-97ba-4539-b0c9-8fc9a554f613","resolution":{"observed_at":"2026-08-14T10:05:24.394081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.369518Z","title":"https://aws.amazon.com/sagemaker/, 2019","venue":null,"work_id":"d55f5482-7ab0-497c-9daf-e83bf5fe245a","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.163903Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:71cdab72a0d09d35f9f552ecbcbea2fe3b013c486e3c359bc2f78a11ddd7b3bf","observation_id":"9a333515-e47e-4f83-b983-65b6b9381876","resolution":{"observed_at":"2026-08-14T10:05:24.375323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.348464Z","title":"https://hadoop.apache.org, 2019","venue":null,"work_id":"d1d44c93-9a81-4e39-a10c-fc5c64001391","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.169219Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:576850df7d48b324a42d747d12f267b053321d33fb746a1e6d55d7e8a4c9f633","observation_id":"c9d3c3b2-d998-462d-9c87-1c8a8f212ed4","resolution":{"observed_at":"2026-08-14T10:05:24.355327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.329773Z","title":"https://azure.microsoft.com/ en-us/services/machine-learning-service/, 2019","venue":null,"work_id":"258a8ba6-35d4-4ecc-bc36-88d603e1cd80","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.174297Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:b1ddd403681eccf453159ad96ce945add69517ecded166434efc284cb6d00a96","observation_id":"cd14c1b7-0cb1-40e2-a915-82e02e2617bc","resolution":{"observed_at":"2026-08-14T10:05:24.335989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.309523Z","title":"https://cloud.google.com/ai-platform/, 2019","venue":null,"work_id":"deba223e-ee94-4937-a8d8-68c37bdb6200","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.179218Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:afc0cd96411909e7362f64c534793394243d5c4c06cd2a5e48b098142bed3184","observation_id":"746e2289-ac1e-4223-bb79-2357526db229","resolution":{"observed_at":"2026-08-14T10:05:24.315479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.287416Z","title":"https://kubeflow.org, 2019","venue":null,"work_id":"db682150-2008-4ff8-813f-f52d0430e435","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.184339Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:cc83f9c4f2c197d74f9d0db7146f39307044364a7f8f5f95c4220e230c50fd67","observation_id":"3a511e8a-f583-476c-93b8-f6a05b135ec3","resolution":{"observed_at":"2026-08-14T10:05:24.294609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.263422Z","title":"https://docs.microsoft.com/en-us/NimbusML, 2019","venue":null,"work_id":"84fc6b98-5be8-41b9-812f-e4ab75b0c25f","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.189802Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:fdeed894cfa2eebc912b7ef78b2fe3fdaf1e96f20328f7527f892ded98f85f83","observation_id":"08322ea6-8ef7-41b5-83b7-d96b6c7ea235","resolution":{"observed_at":"2026-08-14T10:05:24.269454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.246049Z","title":"https://github.com/Microsoft/onnxruntime, 2019","venue":null,"work_id":"0db14c24-0ee5-4837-a87a-f5385d6bcb29","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.196220Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:e6c769035489d9a45960e92defd7ee6c8618ffe4e758dca8750ab28d997a6b5d","observation_id":"52a3c8dd-0678-4ce0-8681-024ce94a9be0","resolution":{"observed_at":"2026-08-14T10:05:24.251952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.228454Z","title":"https://www.microsoft.com/en-us/sql-server/sql-server-2019, 2019","venue":null,"work_id":"6aaa8420-690d-40bc-9c77-040263179e31","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.201520Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:ad6551d28d5182b361db8711690043f75e75c1fd0c96b8db59c05babe7503a76","observation_id":"c1eebc1e-5c29-44b8-83c9-6f3ebbf971a5","resolution":{"observed_at":"2026-08-14T10:05:24.233999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.208610Z","title":"https://pandas.pydata.org/, 2019","venue":null,"work_id":"53b6e216-d972-4831-92c2-3d761b917bd6","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.207449Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:18438f3edd5a53a28272abf95ccd961ba9a3ae582f5d557d61666b5ba3477338","observation_id":"67b27ea4-fc44-4e59-8160-a979147d8d38","resolution":{"observed_at":"2026-08-14T10:05:24.215222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.191192Z","title":null,"venue":null,"work_id":"8ea73802-2f94-40a2-aada-3ee529df4b5c","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.212271Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:8bb4a9963df2797c07a9e0fb257f1fc96f9b72ee84ff93e3a355aea45c2d26ff","observation_id":"2322418f-b70d-40bd-9a73-4af7f7579b93","resolution":{"observed_at":"2026-08-14T10:05:24.196832Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.172162Z","title":"Agarwal, B","venue":null,"work_id":"7606dc3b-0d78-4538-98e3-3f663b121421","year":2009},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.217741Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:d55e9d5cbf8d1b3b82fb3e77ea1f302bfbd149e8ae51df3bc8c7ff8c853c847c","observation_id":"b3a84bda-9dc6-4bb4-818e-646593245b5f","resolution":{"observed_at":"2026-08-14T10:05:24.178855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.154185Z","title":"Ahmed, S","venue":null,"work_id":"75f436f5-1281-43e9-9a92-3f0677c40bba","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.223096Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:f7c6cf4046a0249d0e8705d680c265a12bae5a4695984b4fa9d0f2b13809631a","observation_id":"f6829ff5-799b-4598-b3b0-305db3a560dd","resolution":{"observed_at":"2026-08-14T10:05:24.159516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.137581Z","title":"Atkinson, D","venue":null,"work_id":"cf28c467-0066-42fa-87fa-52aa820fcadc","year":1990},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.228453Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:542dac0fe54b1449d6da906176f6a5679eb94ce986a1a227676e3a5311fb9204","observation_id":"bf8887be-9aa9-452a-bba8-421b37cd6ee8","resolution":{"observed_at":"2026-08-14T10:05:24.142710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.119551Z","title":"https://atlas.apache.org/, 2019","venue":null,"work_id":"38000dc8-c1a6-418a-b217-2eeac0c79811","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.234480Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:197fc1fabc286139264f922879beba41ca8d1d0cee42e892941334292044dba2","observation_id":"f2d7a646-1aad-410a-b6c6-dbd82f0aac2c","resolution":{"observed_at":"2026-08-14T10:05:24.125078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.101804Z","title":"Baylor, E","venue":null,"work_id":"8d94c836-0f4d-41bd-834d-d41a5082460e","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.239762Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:169703bb8f068e6865ce14ef6d072fad8b06d619138d4257b9e36409c90e41bc","observation_id":"4f251bdb-91f2-4589-b320-28f86bd21f61","resolution":{"observed_at":"2026-08-14T10:05:24.107452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.084184Z","title":"Carlini, C","venue":null,"work_id":"5c43f7ed-6770-4abe-8520-e249abed196f","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.244692Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:a29e90c3095bc48363cfaf1adbf44e69f8d56ca44bd2c4a0e9513e0b98ea87a3","observation_id":"7807b411-2768-4130-bc3f-951c8ec8eeb7","resolution":{"observed_at":"2026-08-14T10:05:24.089583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.061965Z","title":null,"venue":null,"work_id":"5d64da0f-c69b-4aa3-9e60-1f11044aba1c","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.249496Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:da6f3fc0846de83eeb9c0a211ff0efd7c91d67da4af8a858d211ed18f479cc7b","observation_id":"f5f07049-3e8f-4853-992d-b631b349d639","resolution":{"observed_at":"2026-08-14T10:05:24.067659Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.040590Z","title":null,"venue":null,"work_id":"e99d017b-4dc8-4ebc-b08a-0cc81df59fd9","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.254131Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:a0d2bdd95161efb4f8f0605b55d40a49b135073880d42e33903b765362ce10fa","observation_id":"4e91585c-ca0d-4797-9dd4-e4d8f7be386b","resolution":{"observed_at":"2026-08-14T10:05:24.049284Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.023851Z","title":"Crankshaw, X","venue":null,"work_id":"87bb7cc5-7a5d-46ea-a48f-0df8089ef8e5","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.258986Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:e3534cea962ad1abe051e3f939bc7fb166e33bf41a3d6a030dab9c90a1fc4f64","observation_id":"88693e4b-5cff-4d33-a09d-43633c7f6ded","resolution":{"observed_at":"2026-08-14T10:05:24.029023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:24.008047Z","title":null,"venue":null,"work_id":"a4b17651-65e1-4caf-8194-5958242d6525","year":2014},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.263760Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:43f4df7fe153edd850decd660bc939882ca943c2905098015f94b5023b447fce","observation_id":"d55e5e1c-938c-4282-b594-a21edb14d306","resolution":{"observed_at":"2026-08-14T10:05:24.012864Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.991199Z","title":"Curino, S","venue":null,"work_id":"0762e14f-d174-414d-93f2-ab030fa01603","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.269115Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:a00e4cd78b30026578ace913695def6a233128c9ed7e90d4088ee74157b97fc0","observation_id":"8cab8fec-b80c-4fa0-8c38-3bc9f7da6e9c","resolution":{"observed_at":"2026-08-14T10:05:23.996264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.971823Z","title":"Floratou, A","venue":null,"work_id":"3120ffee-447a-4bef-bed8-0e20aa6bc822","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.274131Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:dc08b6e1d56b690354458db38e5ef06748c556d4c8e813a077df003673725a70","observation_id":"118ec58d-4eb9-4952-a915-96dccba00c79","resolution":{"observed_at":"2026-08-14T10:05:23.978270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.951200Z","title":"Florescu and D","venue":null,"work_id":"eb3cbd8b-b616-4ee7-9f96-13b955779470","year":1999},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.279140Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:69fb95c038d4c6161f0759e2c015c8907ca7525ace901edd57b6ba624cae71f8","observation_id":"8dcaafd8-14f8-4d2f-824b-42671a0ef164","resolution":{"observed_at":"2026-08-14T10:05:23.956839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.933484Z","title":"https://gdpr-info.eu/, 2016","venue":null,"work_id":"9181b7e1-4c63-4234-b178-92b0cf5ad517","year":2016},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.283886Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:4d2375af82c2d12dc68fdfb9bbc1ab48ba9ff2572dcf12cdd880b1b4476ec248","observation_id":"0ef18786-2491-4856-a6a8-0652176d9086","resolution":{"observed_at":"2026-08-14T10:05:23.939180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.916567Z","title":null,"venue":null,"work_id":"ff14efc3-28da-4964-8ef4-c36c62f43e3a","year":2012},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.288657Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:685f2533e412ff98ec1c25d97df2a17ae610d00602b55b75dce0d7c7e415f093","observation_id":"a7b3b13b-3dbf-4981-980b-e87fb3f67b35","resolution":{"observed_at":"2026-08-14T10:05:23.922006Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.900554Z","title":"Hutchison, B","venue":null,"work_id":"430b48f1-aed7-4e2b-ab64-50dd02a045d8","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.293268Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:a5e1b59930ab6e7085d88249bdad8203a1657b568bcf03f38c94ed1d05f8c4bb","observation_id":"df27db27-6a23-42dc-9294-df6b2f70ac76","resolution":{"observed_at":"2026-08-14T10:05:23.905998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.883858Z","title":"Hutter, L","venue":null,"work_id":"904e8952-9a65-402d-8661-2cf6e329adda","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.298709Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:ab2fcf4bffd5ecc7cb748e963a052478b40a162e7da71332f022cc86e18025e8","observation_id":"a7187434-054e-4666-b31a-515c768348cb","resolution":{"observed_at":"2026-08-14T10:05:23.889193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.717499Z","title":"https://mlflow.org, 2019","venue":null,"work_id":"1733a3bf-b4df-4cd9-9066-094dbcbed3cc","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.344060Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:8991a5535dda36c38e9366799d51e8ddbd2fe41c5184e54394caa965f3f62305","observation_id":"479711f3-93f4-4e3e-a3de-07a25a76c8c6","resolution":{"observed_at":"2026-08-14T10:05:23.724039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.834110Z","title":"Jalaparti, C","venue":null,"work_id":"015ea474-7a86-46b4-862b-6f2077a40c51","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.308541Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:ebcf71563c578fc9e0bc8dc3ea697fc1a06496d66f9b37b65bcb106fbbf6c925","observation_id":"d7b0d3eb-0969-4c7f-ac05-2c4a3a117c2f","resolution":{"observed_at":"2026-08-14T10:05:23.840422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.06590","last_updated":"2019-06-15T16:41:16Z","snapshot_observed_at":"2026-08-14T16:15:07.220883Z","submitted_at":"2019-06-15T16:41:16Z","title":"Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems","version":1},"cited_work":{"arxiv_id":"1906.06590","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.06590","snapshot_observed_at":"2026-08-14T10:05:23.486786Z","title":"Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems","venue":"cs.DB","work_id":"63bf9fea-d00d-49f8-9883-0caec9828bcc","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.313269Z"},"links":{"cited_paper":"/paper/1906.06590","citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:98999283cf7ea81caed14216f7fc2115569d9d5dabbea277768c3bd773c61f50","observation_id":"66e756f9-8479-4007-b0b1-6940e946e127","resolution":{"observed_at":"2026-08-14T10:05:23.492603Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.815886Z","title":null,"venue":null,"work_id":"ce92e413-c50f-4a52-b814-a1280c8d0072","year":2016},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.319221Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:68fee6522ec0e28454628ce854ba96036a960b6538149a6dbf77b05f9179eb78","observation_id":"f1ec246d-34a6-4b63-847c-b43b2f3d313c","resolution":{"observed_at":"2026-08-14T10:05:23.822161Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.797421Z","title":"https://www.kaggle.com/datasets, 2019","venue":null,"work_id":"9ea7c2ed-5e6d-401f-a11d-890d898c573d","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.324066Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:06f9804cf1d100c22fddfb6d20770777fd13932f1adaeb2097b6529d2d968b99","observation_id":"2b858669-3ec3-436f-bfd3-31e05749d013","resolution":{"observed_at":"2026-08-14T10:05:23.802793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.776785Z","title":"Karanasos, M","venue":null,"work_id":"b049f440-9f3c-4a1f-a5d4-59114e3b2b9e","year":2020},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.329230Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:eff701c421fb3bb1f161ef8344b6512ecf02de90ca9f0d1bc86b541a5d9ea54d","observation_id":"57ab0247-1ef9-466e-b2be-bc2aa005db37","resolution":{"observed_at":"2026-08-14T10:05:23.784304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.753403Z","title":"Kunft, A","venue":null,"work_id":"5e363ff2-ccb3-45a7-9386-37dd76096cfd","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.334219Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:dd4ebd9b41f7e98705e4eb24e1835caf004e62bda3cee62efa3351c2eb8151e7","observation_id":"6eebc112-55e8-4ba7-89ba-7efd39bbb68d","resolution":{"observed_at":"2026-08-14T10:05:23.759022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.736055Z","title":null,"venue":null,"work_id":"f0f6e21e-0efb-4e06-b74f-fe2f35d8f57d","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.339360Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:b10b1503031a8080361d2d3e1090e6a59b9bbf45fa2e4c8824d828c0d8f58b44","observation_id":"d38f62b7-59d5-4a04-8739-52520ab47507","resolution":{"observed_at":"2026-08-14T10:05:23.741059Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.593973Z","title":"Siddiqui, A","venue":null,"work_id":"1f283103-7579-497d-a2d7-e03cf414316b","year":2020},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.383767Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:3d94ac6c1c38abd60e8e36b31ec8c5d6ec115a5bb68b21184efdb31324049bb7","observation_id":"e3f91668-c39a-4dc5-9efd-4b732cb6f932","resolution":{"observed_at":"2026-08-14T10:05:23.600502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.697388Z","title":"https://spark.apache.org/docs/latest/ml-guide.html, 2019","venue":null,"work_id":"e620b58b-e98a-4d9c-992b-5f9aaf358299","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.349121Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:d175e7cbcbc062e1050889eda1d277586833dabe898b35891799358e6129d4c5","observation_id":"9ee5347a-2854-4c77-87ac-798d63c98316","resolution":{"observed_at":"2026-08-14T10:05:23.703310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.676773Z","title":"Narayan, V","venue":null,"work_id":"51574e65-f85b-4a6b-ad71-4ba535d8b9c4","year":2011},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.353862Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:57615b91625bd14c50e4ba9315e156a87675922ad81db379800ef8ef8af9372f","observation_id":"bec7420d-58c1-451f-b23e-e6cf89cffa9b","resolution":{"observed_at":"2026-08-14T10:05:23.682114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.652888Z","title":"Olston, F","venue":null,"work_id":"1b8351bd-2f52-4977-82ef-a245bc6dab58","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.358639Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:c8c818102ce019fa119f5161b012d25afa8b29590c1714f259b8e43aa5ef71d2","observation_id":"a07b025d-7b7b-42b3-9950-61cdb05577a3","resolution":{"observed_at":"2026-08-14T10:05:23.662812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.634101Z","title":"https://onnx.ai","venue":null,"work_id":"cd16ebb8-1593-45af-9af5-e007f8a72316","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.363367Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:5e8943b99e0abb9cdda64ea0101480c19e02f407b17fb3d1bd87c840093bbed2","observation_id":"597196de-661a-49a0-8ffa-a4e1d392b677","resolution":{"observed_at":"2026-08-14T10:05:23.640067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.09536","last_updated":"2019-12-19T20:29:44Z","snapshot_observed_at":"2026-08-17T22:52:23.745721Z","submitted_at":"2019-12-19T20:29:44Z","title":"Data Science through the looking glass and what we found there","version":1},"cited_work":{"arxiv_id":"1912.09536","doi":null,"metadata_source":"pith","pith_arxiv_id":"1912.09536","snapshot_observed_at":"2026-08-14T10:05:23.457002Z","title":"Data Science through the looking glass and what we found there","venue":"cs.LG","work_id":"dc93697e-575b-4f6b-9faf-b9762a053f07","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.368165Z"},"links":{"cited_paper":"/paper/1912.09536","citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:17b1adaafec5287250f0ce623a27c9896173e7722718f34510fb6fbb47e7fc3b","observation_id":"dc8b0edd-2a9e-4ac6-8015-75046f45273b","resolution":{"observed_at":"2026-08-14T10:05:23.466345Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.613329Z","title":"Ramachandra, K","venue":null,"work_id":"cf3bd57d-7fd8-4c24-9ae5-a14818aea9c9","year":2017},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.373384Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:0fb8448e3f09e8ac899bce876b44b889b40a9b3b08fc0bac5c8dbb53a9fbf3ae","observation_id":"d0740db5-cebd-43c7-9095-51f4c2046415","resolution":{"observed_at":"2026-08-14T10:05:23.619364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.05799","last_updated":"2018-02-21T04:30:30Z","snapshot_observed_at":"2026-08-14T19:45:22.282120Z","submitted_at":"2018-02-15T23:36:51Z","title":"Horovod: fast and easy distributed deep learning in TensorFlow","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.05799","snapshot_observed_at":"2026-08-14T10:05:23.378301Z","title":"Sergeev and M","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.378301Z"},"links":{"cited_paper":"/paper/1802.05799","citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:6315183a90e043f779998c319b843080b6e0677c3b6fb220e187cd6630c8204d","observation_id":"369b564a-7e51-4295-9f2b-7c0a4f6d6027","resolution":{"observed_at":"2026-08-14T10:05:23.378301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.569560Z","title":"https://tinyurl.com/sqlserver2017, 2019","venue":null,"work_id":"587fdcd4-31b9-43dd-b3aa-e948ecf258ac","year":2019},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.388919Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:7da6d5a949e4eb7fdaae2678320a9e08b8776b2190976b9f0f7962de49a82d03","observation_id":"a2a476da-28f3-45f8-9bcc-4998d228ed42","resolution":{"observed_at":"2026-08-14T10:05:23.575775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.548079Z","title":"Viswanathan, A","venue":null,"work_id":"4d89db33-85bd-43be-96f1-ca11728046be","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.393790Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:4a50065fe9c79f01cdaefd9cc80982418014dfd5816332956280284f39a67726","observation_id":"ebeff1a7-c38e-4983-a031-fd5854c6cc88","resolution":{"observed_at":"2026-08-14T10:05:23.554070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.530164Z","title":null,"venue":null,"work_id":"7672c56b-a615-4b18-a9b0-f3d72a853e97","year":2018},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.399031Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:626499373af03c5841f6ff007f767b86c46a64bda444fbacbd91178706920485","observation_id":"f3c7710d-36f8-4ca9-9b10-f81fcc0082bf","resolution":{"observed_at":"2026-08-14T10:05:23.535499Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:05:23.861793Z","title":null,"venue":null,"work_id":"099e38e8-5a8b-4704-97ca-7383ee607ee0","year":null},"citing_paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-14T10:05:23.303336Z"},"links":{"citing_paper":"/paper/1909.00084"},"observation_digest":"sha256:7d33007af0abb73c002c8cae775b89c90b7183a5e8179c451dad088e1e359dbb","observation_id":"e5ce568a-ebf3-47e1-a5f0-780f07f78c50","resolution":{"observed_at":"2026-08-14T10:05:23.867920Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1909.00084","last_updated":"2019-12-27T23:48:38Z","latest_version":2,"primary_category":"cs.DB","snapshot_observed_at":"2026-08-17T19:37:08.906330Z","submitted_at":"2019-08-30T22:37:15Z","title":"Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":3,"verified_fuzzy":48},"total_outbound_references":62},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:1909.00084."}