A blazing-fast in-memory store used for caching, queues, rate limiting and real-time streams.
Official siteRedis is an in-memory data structure store. Because it keeps data in RAM, reads and writes are sub-millisecond, which makes it the go-to layer for caching, session storage, rate limiting, pub/sub messaging and lightweight queues.
It is more than a key-value cache: it offers rich data types (lists, sets, sorted sets, hashes, streams) that turn common patterns — leaderboards, job queues, event streams — into a few native commands. It can persist to disk, but its heart is speed.
Redis is a single-purpose speed layer. It stores structured values in memory and exposes them through fast, atomic commands. Streams give it a durable append-only log; pub/sub gives it messaging; TTLs make it a natural cache.
We add Redis whenever a system needs a cache in front of a slower database, a distributed rate limiter, a job/stream backbone, or shared ephemeral state across instances. It removes load from the primary datastore cheaply.
Redis lives in RAM, so it is not your source of truth for large or critical data — memory is finite and (depending on config) data can be lost on failure. It complements a primary database; it does not replace one. Treat it as fast, disposable state.
Our crawler uses Redis Streams as its work backbone, coordinating jobs across distributed workers, and we use Redis for caching and rate limiting in the backend. It is the piece that keeps high-throughput paths from hammering the primary database.
A document database that stores flexible, JSON-like records — great when your data is nested and evolving.
The powerful, standards-compliant open-source relational database — the safe default for structured data.
A systems language that delivers C-level performance with memory safety guaranteed at compile time.
Common questions
Straight answers on how this fits your marketing and build.
It can persist to disk and act as a primary store, but its main use is as a fast in-memory layer for caching, queues and streams alongside a durable database. We treat it as speed-critical, mostly disposable state rather than the source of truth.
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