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July 15, 2026ACM SIGOPS Operating Systems Review

PostLearn: Towards A Learned Index For PostgreSQL

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Authors

AFAbrar FuadSVShubham VashisthOBOana Balmau

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Overview

Randomized trial demonstrates performance benefits of learned indexes in relational systems, suggesting efficiency improvements.

Key Points

  • This research aims to explore the integration of learned indexes into relational database systems, focusing on PostgreSQL.
  • Introduced PostLearn, integrating the ALEX+ learned index as a native index access method in PostgreSQL.
  • Detailed design and implementation challenges of embedding a model-based index within PostgreSQL.
  • Conducted performance evaluations comparing PostLearn with the built-in B+-Tree under various workloads.
  • PostLearn achieves up to 1.5x speedups for point lookups and small range scans compared to the built-in B+-Tree.
  • End-to-end performance benefits for PostLearn are considerably lower than those observed in isolation.
  • Demonstration of feasibility for incorporating learned indexes into a relational database architecture.

Cite This Study

Fuad et al. (2026) studied this question.

synapsesocial.com/papers/6a5722f088b21df87547fd3dhttps://doi.org/10.1145/3830422.3830433
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