Analyzing and Comparing Lakehouse Storage Systems
Summary: Systematic comparative analysis of Delta Lake, Apache Hudi, and Apache Iceberg exposing design tradeoffs in metadata, transactions, compaction and read/write paths for lakehouse storage. Provides cross-system performance/feature evaluation across multiple axes and releases LHBench, an open benchmark for reproducible lakehouse design comparisons. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Paras Jain (University of California Berkeley)
- 2. Peter Kraft (Stanford University)
- 3. Conor Power (University of California Berkeley)
- 4. Tathagata Das (Databricks)
- 5. Ion Stoica (University of California Berkeley)
- 6. Matei Zaharia (Stanford University)
BibTeX Citation
@inproceedings{jain_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{Analyzing and Comparing Lakehouse Storage Systems}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Jain, Paras and Kraft, Peter and Power, Conor and Das, Tathagata and Stoica, Ion and Zaharia, Matei},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12 | C-Store: A Column-oriented DBMS | 2005 | VLDB | 0.00069513174 |
| 476 | The Making of TPC-DS | 2006 | VLDB | 0.00017860667 |
| 520 | Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores | 2020 | VLDB | 0.00017136828 |
| 662 | Building a Database on S3 | 2008 | SIGMOD | 0.00015176173 |
| 1,138 | Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics | 2021 | CIDR | 0.00012023643 |
| 1,824 | Photon: A Fast Query Engine for Lakehouse Systems | 2022 | SIGMOD | 9.6734544e-05 |
| 3,336 | White-box Compression: Learning and Exploiting Compact Table Representations | 2020 | CIDR | 7.5084986e-05 |
| 6,076 | Self-Organizing Data Containers | 2022 | CIDR | 5.9852895e-05 |
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|---|---|---|---|---|
| 1 | 10,536 | Active Data Lakes: Regaining Physical Data Independence Without Losing Interoperability | 2026 | VLDB |
| 2 | 3,877 | An Empirical Evaluation of Columnar Storage Formats | 2024 | VLDB |
| 3 | 10,565 | LakeHelm: Zero-Shot Lakehouse Advisor for Joint Engine-Format Selection and Configuration | 2026 | VLDB |
| 4 | 3,071 | Choosing A Cloud DBMS: Architectures and Tradeoffs | 2019 | VLDB |
| 5 | 5,983 | Adaptive and Robust Query Execution for Lakehouses at Scale | 2024 | VLDB |
| 6 | 9,378 | AutoComp: Automated Data Compaction for Log-Structured Tables in Data Lakes | 2025 | SIGMOD |
| 7 | 1,138 | Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics | 2021 | CIDR |
| 8 | 7,780 | Petabyte-Scale Row-Level Operations in Data Lakehouses | 2024 | VLDB |
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| 10 | 520 | Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores | 2020 | VLDB |