ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines
Summary: ELT-Bench: end-to-end benchmark for AI agents to build ELT pipelines—integrating diverse sources, using data tools, writing code/SQL and orchestrating workflows (100 pipelines, 203 models). Eval of 4 agents with 6 LLMs: best agent succeeds on 11.3% of models (avg $1.41, 72.2 steps), exposing major automation gaps. (summarized by gpt-5-mini on Mar 13 2026)
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Authors
- 1. Tengjun Jin
- 2. Yuxuan Zhu
- 3. Daniel Kang
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 167 | The Snowflake Elastic Data Warehouse | 2016 | SIGMOD | 0.00039408116 |
| 366 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.00025580097 |
| 998 | CodeS: Towards Building Open-source Language Models for Text-to-SQL | 2024 | SIGMOD | 0.00014726344 |
| 1,839 | DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing | 2025 | VLDB | 0.00010351287 |
| 3,189 | Text2SQL is Not Enough: Unifying AI and Databases with TAG | 2025 | CIDR | 7.4140094e-05 |
| 4,681 | Cloud Analytics Benchmark | 2023 | VLDB | 5.9953512e-05 |
| 5,115 | TPC-DI: The First Industry Benchmark for Data Integration | 2014 | VLDB | 5.6808821e-05 |
| 5,615 | TPCx-AI - An Industry Standard Benchmark for Artificial Intelligence and Machine Learning Systems | 2023 | VLDB | 5.409e-05 |
| 5,756 | Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System | 2025 | SIGMOD | 5.3387063e-05 |
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