Relational Databases

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Overview

Relational databases organize information into tables connected by keys, with SQL and integrity rules supporting reliable storage, updates, and analysis. Research improves how systems plan and tune queries, protect sensitive data, and integrate or document schemas; newer work also uses language models and agents to translate questions into SQL and explore databases. For learning from relational data, approaches include graph neural networks, relational transformers, and synthetic pretraining, evaluated on tasks such as RelBench as well as SQL benchmarks like Spider and BIRD. A central challenge is making systems dependable across large, unfamiliar schemas and SQL dialects while balancing accuracy, execution cost, privacy, and the complexity of specialized methods.

Latest papers

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80 papers5 papers in the last four weeks, down 50% on the four weeks before. 0.0% of all new papers.

  1. RDL-Bench: A Benchmark for Task-Aware Question Answering over Relational Databases

    Oct 15, 2026Yao Cheng, Siqiang LuoTable QARelational Databases

    College of Computing and Data Science, Nanyang Technological University, Singapore

  2. Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables

    Oct 13, 2026Zhexi FengLLM Agent RoutingTable QA

    Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA

  3. DSABench: Benchmarking Source Discovery, Coordination, and Execution for Multi-Database Agents

    Oct 10, 2026Jinlong Luo, Haoran Wu, Bo XuAgent BenchmarksText-to-SQL

    Institute of Automation, Chinese Academy of Sciences, Beijing, China

  4. CATune: Structural Constraint-Aware Bayesian Optimization for DBMS Configuration Tuning

    Oct 7, 2026Fangping Lan, Qi Zhang, Eduard DragutDatabase SystemsBayesian Optimization

    Temple University Philadelphia, PA, USA

  5. From Benchmarks to Production: A Text-to-SQL System for Complex Financial Data

    Oct 2, 2026Arijit Sehanobish, Bruno Gomes Coelho, Guillaume Michel +3Text-to-SQLFinancial QA

    Kensho Technologies

  6. Closing the Cross-Dialect Gap: Query Plans as a Portable Interface in Text-to-SQL

    Sep 27, 2026Corentin Royer, Robin Oester, Yotam Perlitz +3Text-to-SQLRelational Databases

    IBM Research, Zurich, Switzerland · ETH Zurich, Zurich, Switzerland

  7. KathDB-FAO: Synthesized Query Plans in a Multimodal DBMS

    Sep 23, 2026Guorui Xiao, Douglas Brown, Artur Borycki +1Relational DatabasesDatabase Systems

    University of Washington · Teradata

  8. MetaRTL: Meta-path Attention Enhanced Relational Table Learning

    Sep 17, 2026Ken Zhong, Weichen Li, Zheng WangRelational Deep LearningRelational Databases

    School of Computer Science, Shanghai Jiao Tong University, Shanghai, China · Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai, China

  9. A Hybrid Dependency-Aware Framework for Task Decomposition and Dynamic Agent Generation in Oracle-to-PostgreSQL Migration

    Sep 13, 2026Oleg Grynets, Oleg Kaskun, Alona Seletska +2Code TranslationTask Decomposition

    EPAM Systems McLean, Virginia, USA · EPAM Systems Lviv, Ukraine · EPAM Systems Kyiv, Ukraine

  10. Towards Anticipatory Databases Through Shared Data and Workload Semantics

    Sep 13, 2026Farzaneh Zirak, Kasper Overgaard Mortensen, Farhana Choudhury +1Cache ReplacementSemantic Caching

    University of Melbourne · Aarhus University

  11. Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

    Sep 10, 2026Dong-Jae Koh, Huisu Kim, SeongHwan Yoon +4Multi-Agent LLM SystemsLLM Reliability

    School of Computer Science and Engineering, Kyungpook National University, South Korea

  12. BudgetSchemaBench: A Budget-Swept Diagnostic for Schema Context in Text-to-SQL

    Sep 8, 2026Chen ShenText-to-SQLText-to-SQL Evaluation

    Megagon Labs

  13. Git4Data: Database-Native Version Control for AI Agents

    Sep 2, 2026Hongshen Gou, Zuyu Zhang, Yuze Sun +4Relational Databases

    MatrixOrigin · Purdue University

  14. Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

    Sep 1, 2026Gene ZhangRelational Databases

  15. Relational-Core Graph Analytics Querying graphs at SQL scale, and why the node/edge model is a performance tax, not a truer picture of connected data

    Sep 1, 2026Gene ZhangRelational Databases

    System: ClickGraph / DeltaGraph

  16. Advancing Open and Reproducible Relational Learning: RelArena-αα, TabPFN-Rel and RPI

    Aug 17, 2026Adrian Hayler, Klemens Flöge, Alan Arazi +44Relational Deep LearningRelational Databases

  17. AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMS

    Aug 10, 2026Geonho Lee, Jeongho Park, Donghyoung Han +1Retrieval-Augmented GenerationGraph Retrieval-Augmented Generation

    KAIST Daejeon, Republic of Korea · GraphAI Daejeon, Republic of Korea

  18. Beyond Tables: Doc2DB-Bench for Relationally Faithful Document-to-Database Construction

    Aug 9, 2026Zhuowen Liang, Zhengxuan Zhang, Jiayang Wang +2Document Information ExtractionSynthetic Benchmark Generation

    1The Hong Kong University of Science and Technology (Guangzhou)

  19. Metadata Reconstruction from Values Alone: Recovering Column Semantics in Undocumented Warehouses

    Aug 8, 2026Mike HelwigSelective PredictionText-to-SQL

    Independent Researcher USA

  20. ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB

    Aug 8, 2026Yifan Wu, Yuhan Li, Zhenhua Wang +6Online Resource AllocationRelational Databases

    The State Key Laboratory of Blockchain and Data Security Zhejiang University · Alibaba Cloud Computing

  21. Tytan: Interactive Neurosymbolic Construction of Analytic Semantic Schemas from Relational Data

    Aug 6, 2026Donna Hooshmand, Shubham Shahi, Cameron Barrie +4Semantic MappingNeuro-Symbolic Reasoning

    Northwestern University

  22. ERUnderstand: Evaluating Vision-Language Models on Structured ER Diagrams

    Jul 27, 2026Ali Ansari, Yasmin Mohammadi, Farnoush Nili +3VLM EvaluationDocument Image Understanding

    Temple University · Department of Computer and Information Sciences · Philadelphia, PA, USA

  23. SINT-Flow: Schema Integration using Large Language Model Workflows

    Jul 27, 2026Keti Korini, Christian BizerSemantic MappingRelational Databases

    University of Mannheim Mannheim, Germany

  24. Prompt as a Data Type: In-Database LLM Prompt Management and Rewriting

    Jul 23, 2026Denis Mayr Lima Martins, Gottfried VossenLLM PromptingPrompt Optimization

    Department of Computing and Mathematics University of Sao Paulo Ribeirão Preto, São Paulo, Brazil · Department of Information Systems University of Münster Münster, Germany

  25. Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval

    Jul 14, 2026Qingcheng Zeng, Puxuan Yu, Aman Mehta +2Schema LinkingText-to-SQL

    Northwestern University · Snowflake Inc.

  26. Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass

    Jul 8, 2026Victor Giannakouris, Immanuel TrummerLLM Code GenerationRelational Databases

    Cornell University Ithaca, NY, USA

  27. Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints

    Jul 8, 2026Alan Gany, Bogdan Cautis, Silviu ManiuGraph Neural NetworksAdversarial Attacks

    Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG Grenoble, France

  28. Spider 2.0-AIFunc: Extending Real-World Text-to-SQL to AI-Native SQL Workflows

    Jul 7, 2026Tianyang Liu, Canwen Xu, Fangyu Lei +6Text-to-SQLRelational Databases

    1UC San Diego · *Work done during Tianyang Liu’s internship at Snowflake. · 2Snowflake AI Research +1

  29. Parameter-Free Encoders Remain Viable for RDB Foundation Models

    Jul 6, 2026Linjie Xu, David WipfRelational Foundation ModelsTabular Foundation Models

    University of Hong Kong, Shanghai X-Lab.

  30. A Fair Benchmarking of Deep Relational Database Learning Models

    Jul 4, 2026Kazi F. Akhter, Bharath Ajendla, Manar D. SamadTransformerGraph Representation Learning

    Department of Computer Science Tennessee State University Nashville, TN, USA · SAP AI Research and Innovation SAP Labs Palo Alto, CA, USA