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The SQL++ Query Language: Configurable, Unifying and Semi-structured

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arxiv 1405.3631 v8 pith:DF45HTHN submitted 2014-05-14 cs.DB

classification cs.DB
keywords querylanguagessemi-structuredlanguagesemanticsdatajsonoptions
verification ladder T0 review T1 audit T2 compute T3 formal
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NoSQL databases support semi-structured data, typically modeled as JSON. They also provide limited (but expanding) query languages. Their idiomatic, non-SQL language constructs, the many variations, and the lack of formal semantics inhibit deep understanding of the query languages, and also impede progress towards clean, powerful, declarative query languages. This paper specifies the syntax and semantics of SQL++, which is applicable to both JSON native stores and SQL databases. The SQL++ semi-structured data model is a superset of both JSON and the SQL data model. SQL++ offers powerful computational capabilities for processing semi-structured data akin to prior non-relational query languages, notably OQL and XQuery. Yet, SQL++ is SQL backwards compatible and is generalized towards JSON by introducing only a small number of query language extensions to SQL. Recognizing that a query language standard is probably premature for the fast evolving area of NoSQL databases, SQL++ includes configuration options that formally itemize the semantics variations that language designers may choose from. The options often pertain to the treatment of semi-structuredness (missing attributes, heterogeneous types, etc), where more than one sensible approaches are possible. SQL++ is unifying: By appropriate choices of configuration options, the SQL++ semantics can morph into the semantics of existing semi-structured database query languages. The extensive experimental validation shows how SQL and four semi-structured database query languages (MongoDB, Cassandra CQL, Couchbase N1QL and AsterixDB AQL) are formally described by appropriate settings of the configuration options. Early adoption signs of SQL++ are positive: Version 4 of Couchbase's N1QL is explained as syntactic sugar over SQL++. AsterixDB will soon support the full SQL++ and Apache Drill is in the process of aligning with SQL++.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 25 citations worldwide. Full citation record

  1. Domain-Specific Data Quality Analysis Using Technology-Independent Query Templates

    cs.DB 2026-07 conditional novelty 6.0 of 10

    A model-driven Quality Pattern Model (QPM) lets domain experts instantiate technology-independent quality-analysis templates that compile to XQuery, SPARQL, or Cypher.

  2. SABER: A SQL-Compatible Semantic Document Processing System Based on Extended Relational Algebra

    cs.DB 2025-08 conditional novelty 5.0 of 10

    SABER defines semantic counterparts of relational algebra operators, exposes them as SQL UDFs, and maps them onto LOTUS, DocETL, and Palimpzest, yielding portable semantic queries.

  3. A Functional Data Model and Query Language is All You Need

    cs.DB 2025-07 reject novelty 5.0 of 10

    A vision paper proposing that all data (tuples, relations, databases) be modeled as functions and queried through a functional query language embedded in ordinary programming languages.

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