Redis keeps data in memory, so reads and writes take well under a millisecond. Teams use it for caching, sessions, rate limiting, job queues, leaderboards and pub/sub messaging. Recent versions also include JSON, search and vector sets in the core.
A Redis developer knows when to cache, how long to keep data, and what happens when memory fills up or a node fails. Redis works alongside your main database, not instead of it. Using it as the only store for important data is usually a mistake.
What We Build With It
- Design caching layers with sensible expiry and invalidation rules
- Build job queues, rate limiters and session stores
- Set up replication, Sentinel or Redis Cluster for high availability
- Configure persistence (RDB snapshots, AOF) and memory eviction policies
- Use Redis search, JSON and vector sets for lookup and AI retrieval work
- Diagnose slow commands, hot keys and memory growth
Where It Fits Best
- Caching pages and API responses to reduce database load
- Login sessions and shopping carts
- Background job queues for Rails, Node.js and Python apps
- Real-time leaderboards, counters and live feeds
- Semantic caching and vector search for AI features
Let's build somethingsimple & powerful
Frequently Asked Questions
Is Redis open source again?
Yes. From Redis 8, Redis Open Source can be used under the AGPLv3 open source licence, as well as the RSALv2 and SSPLv1 licences. If you offer Redis as a service to others, check the licence terms with your legal team. Valkey is a BSD-licensed fork if you need that.
Will adding Redis make our app faster?
Only if the slow part is repeated reads of the same data. We profile first. If the real problem is a missing database index or a slow external API, a cache only hides it.
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