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Cuckoo Index: A Lightweight Secondary Index Structure
Summary: CI is an approximate secondary index using a Cuckoo filter with compressed bitmaps to prune partitions for equality lookups in read-only workloads. It reduces space compared to per-partition Bloom filters for low-to-medium cardinality data and remains competitive for high cardinality, with configurable false-positive control.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12238
- Venue
- VLDB
- Year
- 2020
- Pagerank
- 5.5688295e-05
- Overall Rank
- 5,316 | 63.06%
- DOI
-
10.14778/3424573.3424577
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 4,681 |
Cloud Analytics Benchmark |
2023 |
VLDB |
5.9953512e-05 |
| 5,323 |
Can Learned Models Replace Hash Functions? |
2023 |
VLDB |
5.5671086e-05 |
| 6,470 |
Fast Algorithms for Denial Constraint Discovery |
2023 |
VLDB |
5.0439835e-05 |
| 6,971 |
Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses |
2024 |
SIGMOD |
4.8738633e-05 |
| 7,662 |
Optimizing Collections of Bloom Filters within a Space Budget |
2024 |
VLDB |
4.6812878e-05 |
| 8,221 |
Sieve: A Learned Data-Skipping Index for Data Analytics |
2023 |
VLDB |
4.5511941e-05 |
| 8,410 |
Pruning in Snowflake: Working Smarter, Not Harder |
2025 |
SIGMOD |
4.5154358e-05 |
| 8,499 |
Conditional Cuckoo Filters |
2021 |
SIGMOD |
4.4929219e-05 |
| 9,823 |
NEXT: A New Secondary Index Framework for LSM-based Data Storage |
2025 |
SIGMOD |
4.2710095e-05 |
| 10,200 |
RadixGraph: A Fast, Space-Optimized Data Structure for Dynamic Graph Storage |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,415 |
Dynamic Pruning for Recursive Joins |
2025 |
SIGMOD |
4.1905499e-05 |
| 11,010 |
Breathing New Life into An Old Tree: Resolving Logging Dilemma of B+-tree on Modern Computational Storage Drives |
2024 |
VLDB |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059446482 |
| 80 |
Weaving Relations for Cache Performance |
2001 |
VLDB |
0.00055735291 |
| 101 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049778866 |
| 121 |
Improved Query Performance with Variant Indexes |
1997 |
SIGMOD |
0.00045429472 |
| 167 |
The Snowflake Elastic Data Warehouse |
2016 |
SIGMOD |
0.00039408116 |
| 367 |
Small Materialized Aggregates: A Light Weight Index Structure for Data Warehousing |
1998 |
VLDB |
0.00025518228 |
| 1,169 |
SuRF: Practical Range Query Filtering with Fast Succinct Tries |
2018 |
SIGMOD |
0.00013530267 |
| 1,260 |
Data Blocks: Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation |
2016 |
SIGMOD |
0.00012990853 |
| 1,368 |
SlimDB: A Space-Efficient Key-Value Storage Engine For Semi-Sorted Data |
2017 |
VLDB |
0.0001235708 |
| 1,438 |
Benchmarking Learned Indexes |
2021 |
VLDB |
0.00011965956 |
| 1,464 |
Learning Multi-dimensional Indexes |
2020 |
SIGMOD |
0.0001184772 |
| 1,470 |
Processing a Trillion Cells per Mouse Click |
2012 |
VLDB |
0.00011827274 |
| 1,838 |
Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing |
2014 |
VLDB |
0.00010353323 |
| 1,887 |
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads |
2021 |
VLDB |
0.00010201938 |
| 1,993 |
Column Imprints: A Secondary Index Structure |
2013 |
SIGMOD |
9.8403548e-05 |
| 2,868 |
Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations |
2019 |
SIGMOD |
7.9856878e-05 |
| 3,611 |
Column Sketches: A Scan Accelerator for Rapid and Robust Predicate Evaluation |
2018 |
SIGMOD |
6.9178844e-05 |
| 4,157 |
Performance-Optimal Filtering: Bloom Overtakes Cuckoo at High Throughput |
2019 |
VLDB |
6.3935343e-05 |
| 5,341 |
UpBit: Scalable In-Memory Updatable Bitmap Indexing |
2016 |
SIGMOD |
5.5592799e-05 |
| 8,424 |
Tree-Encoded Bitmaps |
2020 |
SIGMOD |
4.5111681e-05 |
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