{
  "schema_version": 2,
  "id": "develop/use-cases",
  "title": "Redis use cases",
  "url": "https://redis.io/docs/latest/develop/use-cases/",
  "summary": "Learn how to implement common use cases with Redis",
  "tags": [
    "docs",
    "develop",
    "stack",
    "oss",
    "rs",
    "rc"
  ],
  "last_updated": "2026-09-16T16:50:30+01:00",
  "children": [
    {
      "id": "develop/use-cases/rate-limiter",
      "summary": "Enforce request quotas across distributed services with Redis",
      "title": "Redis rate limiter",
      "url": "https://redis.io/docs/latest/develop/use-cases/rate-limiter/"
    },
    {
      "id": "develop/use-cases/session-store",
      "summary": "Store web sessions in Redis.",
      "title": "Redis session store",
      "url": "https://redis.io/docs/latest/develop/use-cases/session-store/"
    },
    {
      "id": "develop/use-cases/leaderboard",
      "summary": "Build ranked leaderboards with Redis sorted sets and user metadata",
      "title": "Redis leaderboard",
      "url": "https://redis.io/docs/latest/develop/use-cases/leaderboard/"
    },
    {
      "id": "develop/use-cases/time-series-dashboard",
      "summary": "Build a rolling sensor graph demo with Redis time series data",
      "title": "Rolling sensor graph demo with Redis",
      "url": "https://redis.io/docs/latest/develop/use-cases/time-series-dashboard/"
    },
    {
      "id": "develop/use-cases/cache-aside",
      "summary": "Cache database reads in Redis with TTL-bounded staleness.",
      "title": "Redis cache-aside",
      "url": "https://redis.io/docs/latest/develop/use-cases/cache-aside/"
    },
    {
      "id": "develop/use-cases/job-queue",
      "summary": "Run a reliable background job queue with Redis.",
      "title": "Redis job queue",
      "url": "https://redis.io/docs/latest/develop/use-cases/job-queue/"
    },
    {
      "id": "develop/use-cases/prefetch-cache",
      "summary": "Pre-load reference data into Redis so every read is a cache hit.",
      "title": "Redis prefetch cache",
      "url": "https://redis.io/docs/latest/develop/use-cases/prefetch-cache/"
    },
    {
      "id": "develop/use-cases/pub-sub",
      "summary": "Broadcast real-time events to many consumers with Redis pub/sub.",
      "title": "Redis pub/sub messaging",
      "url": "https://redis.io/docs/latest/develop/use-cases/pub-sub/"
    },
    {
      "id": "develop/use-cases/streaming",
      "summary": "Process ordered event streams with consumer groups, replay, and configurable retention.",
      "title": "Redis streaming",
      "url": "https://redis.io/docs/latest/develop/use-cases/streaming/"
    },
    {
      "id": "develop/use-cases/recommendation-engine",
      "summary": "Serve personalized recommendations under tight latency budgets by combining vector similarity with structured filters in a single Redis call.",
      "title": "Redis recommendation engine",
      "url": "https://redis.io/docs/latest/develop/use-cases/recommendation-engine/"
    },
    {
      "id": "develop/use-cases/feature-store",
      "summary": "Serve pre-computed ML features on the request path under tight latency budgets, with batch and streaming features kept fresh in the same store.",
      "title": "Redis feature store",
      "url": "https://redis.io/docs/latest/develop/use-cases/feature-store/"
    },
    {
      "id": "develop/use-cases/semantic-cache",
      "summary": "Reuse LLM responses for queries that are semantically similar, not just byte-identical, to cut token costs, reduce latency, and share validated answers across users and sessions.",
      "title": "Redis semantic cache",
      "url": "https://redis.io/docs/latest/develop/use-cases/semantic-cache/"
    },
    {
      "id": "develop/use-cases/memory-layer",
      "summary": "Persistent memory that spans sessions and tasks — working memory per thread, long-term semantic recall, and a time-ordered event log — on a single Redis instance, with sub-millisecond reads on the agent loop's hot path.",
      "title": "Redis as a memory layer",
      "url": "https://redis.io/docs/latest/develop/use-cases/memory-layer/"
    }
  ],
  "page_type": "content",
  "content_hash": "e9259d90520c1ee0b2d6ce6c9aa2a8530bf5e00485ae91b0054c2c297b31a612",
  "sections": [
    {
      "id": "overview",
      "title": "Overview",
      "role": "overview",
      "text": "This section provides practical examples and reference implementations for common Redis use cases."
    },
    {
      "id": "available-use-cases",
      "title": "Available use cases",
      "role": "content",
      "text": "* [Rate limiting](https://redis.io/docs/latest/develop/use-cases/rate-limiter) - Implement token bucket rate limiting with Redis\n* [Session storage](https://redis.io/docs/latest/develop/use-cases/session-store) - Store web sessions in Redis with TTL-based expiration\n* [Time series dashboard](https://redis.io/docs/latest/develop/use-cases/time-series-dashboard) - Build a rolling sensor graph demo with Redis time series data\n* [Leaderboards](https://redis.io/docs/latest/develop/use-cases/leaderboard) - Build a ranked leaderboard with sorted sets and user metadata\n* [Cache-aside](https://redis.io/docs/latest/develop/use-cases/cache-aside) - Cache database reads in Redis with TTL-bounded staleness\n* [Job queue](https://redis.io/docs/latest/develop/use-cases/job-queue) - Run a reliable background job queue with at-least-once delivery and visibility-timeout reclaim\n* [Prefetch cache](https://redis.io/docs/latest/develop/use-cases/prefetch-cache) - Pre-load reference data into Redis so every read is a cache hit, kept current by a CDC sync worker\n* [Pub/sub messaging](https://redis.io/docs/latest/develop/use-cases/pub-sub) - Broadcast real-time events to many consumers with channel and pattern subscriptions\n* [Streaming](https://redis.io/docs/latest/develop/use-cases/streaming) - Process ordered event streams with consumer groups, replay, and configurable retention\n* [Recommendation engine](https://redis.io/docs/latest/develop/use-cases/recommendation-engine) - Serve personalized recommendations under tight latency budgets by combining vector similarity with structured filters in a single Redis call\n* [Feature store](https://redis.io/docs/latest/develop/use-cases/feature-store) - Serve pre-computed ML features on the request path with mixed batch-and-streaming freshness using per-field TTL\n* [Semantic cache](https://redis.io/docs/latest/develop/use-cases/semantic-cache) - Reuse LLM responses for semantically similar queries to cut token costs and skip multi-second model calls on near-duplicate prompts\n* [Memory layer](https://redis.io/docs/latest/develop/use-cases/memory-layer) - Give AI agents persistent memory that spans sessions and tasks — working memory per thread, long-term semantic recall, and a time-ordered event log on one Redis instance"
    }
  ],
  "examples": []
}