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GlassDB: An Efficient Verifiable Ledger Database System Through Transparency

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arxiv 2207.00944 v3 pith:KRGPD4XM submitted 2022-07-03 cs.DB

classification cs.DB
keywords verifiableglassdbtransparencyledgerdatabasedatabasesdataefficient
verification ladder T0 review T1 audit T2 compute T3 formal

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Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs -- a simple abstraction allowing users to verify that a log maintained by an untrusted server is append-only. They expose a simple key-value interface. Building a practical database from transparency logs, on the other hand, remains a challenge. In this paper, we explore the design space of verifiable ledger databases along three dimensions: abstraction, threat model, and performance. We survey existing systems and identify their two limitations, namely, the lack of transaction support and the inferior efficiency. We then present GlassDB, a distributed database that addresses these limitations under a practical threat model. GlassDB inherits the verifiability of transparency logs, but supports transactions and offers high performance. It extends a ledger-like key-value store with a data structure for efficient proofs, and adds a concurrency control mechanism for transactions. GlassDB batches independent operations from concurrent transactions when updating the core data structures. In addition, we design a new benchmark for evaluating verifiable ledger databases, by extending YCSB and TPC-C benchmarks. Using this benchmark, we compare GlassDB against four baselines: reimplemented versions of three verifiable databases, and a verifiable map backed by a transparency log. Experimental results demonstrate that GlassDB is an efficient, transactional, and verifiable ledger database.

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. QMDB: Quick Merkle Database

    cs.NI 2025-01 conditional novelty 6.0 of 10

    QMDB uses append-only twigs and an in-memory index to make blockchain state updates and proof generation faster, reporting up to 2.28 million updates per second, with benchmark caveats.

  2. gECC: A GPU-based high-throughput framework for Elliptic Curve Cryptography

    cs.CR 2024-12 conditional novelty 6.0 of 10

    gECC batches elliptic-curve operations and reduces integer multiply-add instructions to achieve multi-fold ECDSA/ECDH throughput gains on Nvidia GPUs.

  3. PoneglyphDB: Efficient Non-interactive Zero-Knowledge Proofs for Arbitrary SQL-Query Verification

    cs.DB 2024-11 reject novelty 5.0 of 10

    A database system that uses PLONKish/Halo2 zero-knowledge circuits to prove SQL query results are correct without revealing the private database, with TPC-H experiments against ZKSQL and Libra.

  4. Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines

    cs.CR 2026-01 reject novelty 3.0 of 10

    The paper proposes a security layer that signs, freshness-checks, policy-validates, and Merkle-logs MCP tool-use manifests before LLM execution, reporting near-linear scaling and low overhead.

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