Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses
Summary: Predicate caching is a query-driven secondary index for cloud data warehouses, speeding repetitive scans and joins. Lightweight, on-the-fly index built online; implemented in Redshift, delivering up to 10x query speed with minimal build cost. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tobias Schmidt
- 2. Andreas Kipf
- 3. Dominik Horn
- 4. Gaurav Saxena
- 5. Tim Kraska
Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,923 | Efficient B-tree Based Indexing for Cloud Data Processing | 2010 | VLDB | 4.6155204e-05 |
| 3,844 | The evolution of Amazon Redshift (extended abstract) | 2021 | VLDB | 6.7076451e-05 |
| 329 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD | 0.00027249545 |
| 4,455 | Generalized Scale Independence Through Incremental Precomputation | 2013 | SIGMOD | 6.171182e-05 |
| 5,301 | ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data | 2018 | VLDB | 5.5790928e-05 |
| 10,847 | Sampling-based Predictive Database Buffer Management | 2025 | VLDB | 4.1945683e-05 |
| 1,989 | Column Imprints: A Secondary Index Structure | 2013 | SIGMOD | 9.8478437e-05 |
| 7,693 | Processing and Optimizing Main Memory Spatial-Keyword Queries | 2016 | VLDB | 4.6759281e-05 |
| 8,781 | Accelerate Distributed Joins with Predicate Transfer | 2025 | SIGMOD | 4.4534753e-05 |
| 5,832 | Stage: Query Execution Time Prediction in Amazon Redshift | 2024 | SIGMOD | 5.3111109e-05 |