Deep Lake: a Lakehouse for Deep Learning
Summary: Deep Lake extends lakehouse semantics to multimodal deep-learning data by storing images, video, annotations, and tables as tensors. It enables network streaming directly to tensor queries, browser visualization, and PyTorch/TensorFlow/JAX pipelines while preserving GPU utilization. (summarized by gpt-5.6-luna on Jul 21 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sasun Hambardzumyan (Activeloop)
- 2. Abhinav Tuli (Activeloop)
- 3. Levon Ghukasyan (Activeloop)
- 4. Fariz Rahman (Activeloop)
- 5. Hrant Topchyan (Activeloop)
- 6. David Isayan (Activeloop)
- 7. Mark McQuade (Activeloop)
- 8. Mikayel Harutyunyan (Activeloop)
- 9. Tatevik Hakobyan (Activeloop)
- 10. Ivo Stranic (Activeloop)
- 11. Davit Buniatyan (Activeloop)
BibTeX Citation
@inproceedings{hambardzumyan_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{Deep Lake: a Lakehouse for Deep Learning}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Hambardzumyan, Sasun and Tuli, Abhinav and Ghukasyan, Levon and Rahman, Fariz and Topchyan, Hrant and Isayan, David and McQuade, Mark and Harutyunyan, Mikayel and Hakobyan, Tatevik and Stranic, Ivo and Buniatyan, Davit},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,772 | SAP HANA Cloud: Data Management for Modern Enterprise Applications | 2025 | SIGMOD | 5.2209769e-05 |
| 10,997 | The HANA Native Query Engine for Lakehouse Systems | 2025 | VLDB | 5.093636e-05 |
| 11,006 | Magnus: A Holistic Approach to Data Management for Large-Scale Machine Learning Workloads | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 66 | The Snowflake Elastic Data Warehouse | 2016 | SIGMOD | 0.00038561587 |
| 237 | Amazon Redshift and the Case for Simpler Data Warehouses | 2015 | SIGMOD | 0.0002369895 |
| 286 | Milvus: A Purpose-Built Vector Data Management System | 2021 | SIGMOD | 0.00022357911 |
| 520 | Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores | 2020 | VLDB | 0.00017136828 |
| 669 | The TileDB Array Data Storage Manager | 2017 | VLDB | 0.00015163245 |
| 1,138 | Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics | 2021 | CIDR | 0.00012023643 |
| 1,757 | Velox: Meta's Unified Execution Engine | 2022 | VLDB | 9.8166984e-05 |
| 1,824 | Photon: A Fast Query Engine for Lakehouse Systems | 2022 | SIGMOD | 9.6734544e-05 |
| 2,823 | Query Processing on Tensor Computation Runtimes | 2022 | VLDB | 8.0893814e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,457 | Analyzing and Comparing Lakehouse Storage Systems | 2023 | CIDR |
| 2 | 1,138 | Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics | 2021 | CIDR |
| 3 | 6,708 | Serving Deep Learning Models with Deduplication from Relational Databases | 2022 | VLDB |
| 4 | 11,937 | CoreKG: a Knowledge Lake Service | 2018 | VLDB |
| 5 | 4,649 | BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse | 2024 | SIGMOD |
| 6 | 8,979 | Cerebro: A Layered Data Platform for Scalable Deep Learning | 2021 | CIDR |
| 7 | 4,067 | Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches | 2021 | VLDB |
| 8 | 4,592 | Data Platform for Machine Learning | 2019 | SIGMOD |
| 9 | 3,073 | DeepJoin: Joinable Table Discovery with Pre-trained Language Models | 2023 | VLDB |
| 10 | 13,375 | Reimagining Deep Learning Systems Through the Lens of Data Systems | 2024 | VLDB |