Enzyme Demo: Incremental View Maintenance for Data Engineering
Summary: Enzyme is an industrial IVM engine for Spark Declarative Pipelines, providing broad ETL coverage without hand-tuned refresh policies. It supports nondeterministic temporal filters, upgrade-stable multilingual fingerprinting, and history-driven refresh optimization across materialized-view DAGs. (summarized by gpt-5.6-luna on Aug 28 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yuhong Chen (Databricks)
- 2. Ritwik Yadav (Databricks)
- 3. Min Yang (Databricks)
- 4. Supun Abeysinghe (Databricks)
- 5. Manuel Ung (Databricks)
- 6. Jeffrey Helt (Databricks)
- 7. Michael Armbrust (Databricks)
- 8. Shrikanth Shankar (Databricks)
BibTeX Citation
@article{chen_vldb26,
title = {{Enzyme Demo: Incremental View Maintenance for Data Engineering}},
author = {Chen, Yuhong and Yadav, Ritwik and Yang, Min and Abeysinghe, Supun and Ung, Manuel and Helt, Jeffrey and Armbrust, Michael and Shankar, Shrikanth},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4818--4821},
doi = {10.14778/3827998.3828130},
url = {https://doi.org/10.14778/3827998.3828130},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,036 | The Dataflow Model Revisited Or: That Feeling When You Realize Every Problem You've Been Solving Is a Database Problem | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 23 | Spark SQL: Relational Data Processing in Spark | 2015 | SIGMOD | 0.00055406774 |
| 62 | Maintaining Views Incrementally | 1993 | SIGMOD | 0.00039045511 |
| 246 | Deriving Production Rules for Incremental View Maintenance | 1991 | VLDB | 0.00023212582 |
| 408 | DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views | 2012 | VLDB | 0.00018900199 |
| 3,673 | DBSP: Automatic Incremental View Maintenance for Rich Query Languages | 2023 | VLDB | 7.1092596e-05 |
| 7,267 | What's the Difference? Incremental Processing with Change Queries in Snowflake | 2023 | SIGMOD | 5.5698185e-05 |
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| 2 | 5,822 | SnappyData: A Hybrid Transactional Analytical Store Built On Spark | 2016 | SIGMOD |
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| 5 | 6,219 | Incremental View Maintenance For Collection Programming | 2016 | PODS |
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| 7 | 9,832 | [Demo] Low-latency Spark Queries on Updatable Data | 2019 | SIGMOD |
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