# How ScyllaDB's Trie-Based Index Delivers Up to 3X More Throughput

DevFeed: [How ScyllaDB's Trie-Based Index Delivers Up to 3X More Throughput](<https://devfeed.tech/articles/how-scylladb-s-trie-based-index-delivers-up-to-3x-more-throughput-4868.md>)

Original publisher: [Read original article](<https://www.scylladb.com/2026/06/30/trie-index-3x-more-throughput/>)

Author: Tzach Livyatan

Published: 2026-06-30T13:03:08Z

Content type: article

Language: en

Sources: [ScyllaDB](<https://devfeed.tech/sources/scylladb.md>)

Topics: [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [IO](<https://devfeed.tech/topics/io.md>), [Seastar](<https://devfeed.tech/topics/seastar.md>), [2026.2](<https://devfeed.tech/topics/2026-2.md>), [Apache Cassandra](<https://devfeed.tech/topics/cassandra.md>)

Tags: [2026-2](<https://devfeed.tech/tags/2026-2.md>), [apache](<https://devfeed.tech/tags/apache.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [cache](<https://devfeed.tech/tags/cache.md>), [cassandra](<https://devfeed.tech/tags/cassandra.md>), [deep-dive](<https://devfeed.tech/tags/deep-dive.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [latency](<https://devfeed.tech/tags/latency.md>), [memory](<https://devfeed.tech/tags/memory.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [product](<https://devfeed.tech/tags/product.md>), [seastar](<https://devfeed.tech/tags/seastar.md>), [storage](<https://devfeed.tech/tags/storage.md>), [time](<https://devfeed.tech/tags/time.md>)

## AI overview

ScyllaDB's Trie-based SSTable index replaces separate summary and index files with a prefix tree. The article explains the format change, its storage layout and lookup behavior, and reports benchmark results showing 30% to 230% higher throughput and 31% to 63% lower latency than legacy indexes across four read workloads.

## Source excerpt

By transitioning from separate summary and index files to a prefix tree, we optimized cache efficiency, reduced disk I/O, and reduced memory overhead