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Databases·expert

Redis

In-memory data structure store

Redis is essential for caching, session management, and real-time features. I implement sophisticated caching strategies and use Redis data structures for optimal performance.

7+years in production
50+projects shipped
expertproficiency

My take

Why I use Redis

Redis is the Swiss Army knife of data layers. Caching, rate limiting, queues, leaderboards, pub/sub - it does each one well, in microseconds, with primitives I can reason about.

Want the broader stack philosophy? Read about how Sri picks tools or browse engineering insights.

Honest assessment

Strengths & tradeoffs

No tool is perfect. Here's what shines and what to watch for.

Strengths

  • Sub-millisecond latency for reads and writes
  • Rich data structures - sorted sets, streams, hashes
  • Built-in pub/sub and Lua scripting
  • Cluster mode for horizontal scaling
  • Trivial to operate for typical workloads

Tradeoffs (honestly)

  • Memory-bound - dataset must fit in RAM (or close)
  • Persistence options (RDB/AOF) involve tradeoffs
  • Recent license changes (Redis 7.4+) push some users to Valkey
  • Single-threaded core for most operations

Fit assessment

When to reach for Redis

Pick the right tool for the job.

Best fits

Application-level caching

Session storage

Rate limiting and throttling

Real-time leaderboards and counters

Lightweight job queues (BullMQ)

Not ideal for

Primary durable storage for critical data

Datasets too large to fit in RAM

Complex relational queries

Common use cases

CachingSession storageRate limitingPub/sub

Resources

Learn more

Curated official docs, tutorials, and writing on Redis.

Need help with Redis?

Whether you're starting fresh or optimizing an existing implementation, I can help you get the most out of this technology. Read more in insights or get in touch.

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