The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds
Summary: PGM-index is a dynamic, compressed learned index with provable bounds for predecessor, range queries and updates. Distribution-aware, repetition-based compression and multicriteria auto-tuning enable large space reductions with competitive times vs B+-trees. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 50 of 69 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 102 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049545203 |
| 238 | Cache Conscious Indexing for Decision-Support in Main Memory | 1999 | VLDB | 0.00031642425 |
| 801 | SageDB: A Learned Database System | 2019 | CIDR | 0.00016505496 |
| 1,035 | Bitmap Index Design and Evaluation | 1998 | SIGMOD | 0.00014532778 |
| 1,375 | FITing-Tree: A Data-aware Index Structure | 2019 | SIGMOD | 0.00012303141 |
| 1,913 | BF-Tree: Approximate Tree Indexing | 2014 | VLDB | 0.00010113937 |
| 2,041 | Indexable PLA for Efficient Similarity Search | 2007 | VLDB | 9.6992894e-05 |
| 2,051 | Efficient Parallel Lists Intersection and Index Compression Algorithms using Graphics Processing Units | 2011 | VLDB | 9.686731e-05 |
| 2,394 | Building a Bw-Tree Takes More Than Just Buzz Words | 2018 | SIGMOD | 8.9001843e-05 |
| 2,862 | An Experimental Study of Bitmap Compression vs. Inverted List Compression | 2017 | SIGMOD | 7.9898539e-05 |
| 3,488 | Optimal Column Layout for Hybrid Workloads | 2019 | VLDB | 7.0479329e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,182 | On Two-Dimensional Indexability and Optimal Range Search Indexing (Extended Abstract) | 1999 | PODS | 0.00013455963 |
| 6,229 | When Tree Meets Hash: Reducing Random Reads for Index Structures on Persistent Memories | 2023 | SIGMOD | 5.1463389e-05 |
| 8,811 | Tuning Hierarchical Learned Indexes on Disk and Beyond | 2022 | SIGMOD | 4.4441574e-05 |
| 5,157 | Hist-Tree: Those Who Ignore It Are Doomed to Learn | 2021 | CIDR | 5.6589595e-05 |
| 1,460 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011887068 |
| 7,390 | Making In-Memory Learned Indexes Efficient on Disk | 2024 | SIGMOD | 4.7431654e-05 |
| 5,074 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB | 5.7175726e-05 |
| 6,445 | Updatable Learned Indexes Meet Disk-Resident DBMS - From Evaluations to Design Choices | 2023 | SIGMOD | 5.0589805e-05 |
| 8,767 | Dynamic Indexability and Lower Bounds for Dynamic One-Dimensional Range Query Indexes | 2009 | PODS | 4.456315e-05 |
| 9,746 | Why Are Learned Indexes So Effective but Sometimes Ineffective? | 2025 | VLDB | 4.2897489e-05 |