Valkey (Redis-compatible) in-memory data store for caching, session storage, pub/sub, queues, and distributed locks. Use when configuring Valkey or Redis-compatible caching, choosing eviction policies, implementing rate limiting, setting up pub/sub or streams, writing Docker Compose services, migrating from Redis, or tuning performance. Use for valkey, redis, cache, session, pub/sub, streams, distributed-lock, rate-limit, sorted-set.
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---
name: valkey
description: 'Valkey (Redis-compatible) in-memory data store for caching, session storage, pub/sub, queues, and distributed locks. Use when configuring Valkey or Redis-compatible caching, choosing eviction policies, implementing rate limiting, setting up pub/sub or streams, writing Docker Compose services, migrating from Redis, or tuning performance. Use for valkey, redis, cache, session, pub/sub, streams, distributed-lock, rate-limit, sorted-set.'
license: MIT
metadata:
author: oakoss
version: '1.0'
source: 'https://valkey.io/commands/'
user-invocable: false
---
# Valkey
Open-source, Redis-compatible in-memory data store maintained by the Linux Foundation. Forked from Redis OSS 7.2.4 (BSD 3-Clause license). Drop-in replacement for Redis OSS 2.x through 7.2.x — same protocol, commands, and data formats.
**When to use**: Caching, session storage, rate limiting, pub/sub messaging, task queues, leaderboards, distributed locks, real-time counters, or any workload requiring sub-millisecond key-value operations.
**When NOT to use**: Primary relational data store, large object storage (>512 MB values), workloads requiring strong ACID transactions across multiple keys without Lua scripting.
## Quick Reference
| Task | Approach | Key Point |
| ------------------ | -------------------------------------------------------- | --------------------------------------- |
| Cache-aside | `GET` -> miss -> DB read -> `SET key val EX ttl` | Always set a TTL, even a long one |
| Session storage | `HSET session:{id} field val` + `EXPIRE` | Sliding TTL on each request |
| Rate limiting | `INCR` + `EXPIRE` (fixed window) or sorted set (sliding) | Sorted set for precision |
| Distributed lock | `SET lock:{res} token NX PX 30000` | Always set expiry to prevent deadlocks |
| Queue (simple) | `LPUSH` + `BRPOP` | Blocking pop with timeout |
| Queue (reliable) | Streams + `XGROUP` + `XACK` | Consumer groups for at-least-once |
| Pub/Sub | `SUBSCRIBE` / `PUBLISH` | Fire-and-forget, no persistence |
| Streams | `XADD` + `XREADGROUP` | Persistent, replayable, consumer groups |
| Leaderboard | Sorted set: `ZADD` / `ZREVRANGE` | O(log N) rank operations |
| Unique count | `PFADD` + `PFCOUNT` (HyperLogLog) | ~12 KB memory, 0.81% error |
| Eviction policy | `maxmemory-policy allkeys-lru` | Best default for most workloads |
| Docker setup | `valkey/valkey:8.1-alpine` | Health check: `valkey-cli ping` |
| Persistence | AOF (`appendonly yes`) + RDB snapshots | AOF for durability, RDB for backups |
| Client library | `ioredis` or `iovalkey` (official fork) | All Redis clients work unchanged |
| Migrate from Redis | Swap binary, keep data files | RDB/AOF compatible through Redis 7.2 |
## Common Mistakes
| Mistake | Correct Pattern |
| -------------------------------------- | ------------------------------------------------ |
| Using `KEYS *` in production | Use `SCAN` with cursor for iteration |
| No TTL on cache keys | Always set TTL — unbounded growth causes OOM |
| `DEL` on large keys blocking server | Use `UNLINK` for async deletion |
| Pub/Sub for durable messaging | Use Streams with consumer groups for persistence |
| Same TTL on all keys (thundering herd) | Add jitter: `EX (base + random(0, spread))` |
| No `maxmemory` set in production | Set `maxmemory` + eviction policy explicitly |
| Using `MULTI/EXEC` for locking | Use `SET ... NX PX` for distributed locks |
| Storing large blobs (>1 MB values) | Store references; keep values small |
| No health check in Docker Compose | Add `valkey-cli ping` health check |
| Ignoring `requirepass` in production | Always set authentication + ACLs |
## Delegation
- **Discover caching patterns and data model review**: Use `Explore` agent
- **Plan migration strategy from Redis to Valkey**: Use `Plan` agent
- **Implement full caching layer with tests**: Use `Task` agent
> If the `docker` skill is available, delegate Compose networking and multi-stage build patterns to it.
> If the `performance-optimizer` skill is available, delegate application-level caching strategy to it.
> If the `database-security` skill is available, delegate ACL and TLS configuration review to it.
## References
- [Data structures and commands](references/data-structures.md) -- Strings, hashes, lists, sets, sorted sets, streams, HyperLogLog, bitmaps, geospatial
- [Caching patterns](references/caching-patterns.md) -- Cache-aside, write-through, TTL strategies, eviction policies, client-side caching, invalidation
- [Common patterns](references/common-patterns.md) -- Rate limiting, distributed locks, queues, session storage, pub/sub, streams, leaderboards
- [Docker and deployment](references/docker-and-deployment.md) -- Compose setup, persistence, replication, Sentinel, Cluster, security, migration from Redis