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Redis Array Data Structure

2 posts · May 2026 – Jun 2026

What this trail covers

Redis 8.8 introduces a new general-purpose array data structure, offering index-addressable collections of string values. Arrays are dynamic, sparse-friendly, and compute-aware, supporting ring buffer semantics, server-side aggregation (SUM, MIN, MAX, AND, OR, XOR), and search capabilities. Benchmarks show arrays offer significantly better random element access performance compared to lists and competitive performance with hashes, with a moderate increase in memory usage. They are ideal for use cases requiring fast indexed access, sliding windows, server-side aggregation, or element searching. The post also details performance improvements in core data types and operations, a new window counter rate limiter, streams message NACKing, subkey notifications for hash fields, explicit control over JSON numeric array storage, multiple aggregators in a single time series query, and a new COUNT aggregator for sorted sets union and intersection.

All Redis trails
  1. Redis array data type: How it works and when to use itThis post introduces and details the new Redis array data type, explaining its design principles, use cases, and performance characteristics. It covers specific commands like ARGETRANGE, ARSCAN, ARCOUNT, ARLEN, ARRING, and ARLASTITEMS, and provides examples for document line indexing, stack trace analysis, workflow step tracking, network port allocation, fixed-size event logs, and pattern search across sparse data. It also compares the array type's performance and memory usage to lists and hashes, highlighting its advantages for index-addressable collections and sparse data.
  2. Redis 8.8: New array data structure & open source featuresThis post introduces the new general-purpose array data structure in Redis 8.8. It details its capabilities, including dynamic sizing, sparse-friendliness, ring buffer semantics, server-side aggregation (SUM, MIN, MAX, AND, OR, XOR), and search functionality. Benchmarks are provided comparing array performance (random element access, ring buffer inserts) against lists and hashes, highlighting significant throughput advantages for arrays in random access and ring buffer operations. Memory usage comparisons are also presented. The post also briefly mentions other features in Redis 8.8 such as a rate limiter, streams message NACKing, subkey notifications, JSON numeric array storage control, multiple time series aggregators, and a COUNT aggregator for sorted set operations, along with overall performance improvements.