Best of Redis — April 2025

  1. 1
    Video
    Avatar of wdsWeb Dev Simplified·1y

    Every Senior Developer Needs To Know This!

    Understanding and implementing background jobs or job queuing systems can significantly optimize server performance by offloading non-critical tasks from the main request flow. This concept allows tasks such as sending emails or saving information to a file-based system to be processed in the background, reducing the wait time for users. The post explains the architecture and implementation of a Redis-based job queue system, including priority handling, delayed jobs, and retry mechanisms.

  2. 2
    Article
    Avatar of communityCommunity Picks·1y

    Redis Deep Dive for System Design Interviews

    Redis is a versatile and simple tool ideal for system design interviews due to its diverse capabilities and ease of understanding. It supports various data structures and communication patterns, making it suitable for high-speed caching, distributed locking, rate limiting, and proximity searches. Nevertheless, its in-memory nature means it lacks durability, requiring careful consideration in design decisions.

  3. 3
    Article
    Avatar of towardsdevTowards Dev·1y

    Introduction to Redis (Part 1)

    Redis is an open-source, in-memory data structure store used as a database, cache, and message broker. It supports various data structures such as strings, hashes, and lists. Redis is known for its high performance, flexibility, and durability. It offers features like in-memory storage with persistence options, multi-language support, and scalability through master-slave replication. Redis can act as both a secondary database for caching and a primary database for modern applications.

  4. 4
    Article
    Avatar of ramp_engRamp Engineering·1y

    Rate limiting with Redis

    Rate limiting is crucial in managing API usage and prevents overloading systems. Different rate limiting algorithms such as fixed-window, sliding window, leaky bucket, and GCRA offer various benefits and pitfalls. Ramp chose the GCRA algorithm for its efficiency and ease of implementation with Redis, tailoring it to handle multiple use cases. They continue to expand its application and monitor its performance.

  5. 5
    Video
    Avatar of communityCommunity Picks·1y

    Redis Streams vs Pub/Sub: Performance

    This post compares the performance of Redis Streams and Redis Pub/Sub by running a benchmark on AWS. It highlights the primary differences, emphasizes the stateless nature of Pub/Sub, and contrasts it with the durability of Redis Streams. The benchmark tests measure latency, throughput, and CPU usage, revealing that Pub/Sub can handle over 1 million messages per second with lower resources, while Streams provide higher durability at the cost of increased CPU usage and reduced throughput.

  6. 6
    Article
    Avatar of bunBun·1y

    Bun v1.2.9

    Bun v1.2.9 release fixes 48 bugs and introduces Bun.redis, a built-in Redis client, support for ListObjectsV2 in Bun.S3Client, and additional libuv symbols. Enhancements include support for require.extensions and require.resolve paths, a WebKit upgrade, performance improvements in array handling, and several bug fixes across node:http, AsyncLocalStorage, node:crypto, diffieHellman, and more. New options like maxBuffer in Bun.spawn and improved socket field support were also added.

  7. 7
    Video
    Avatar of dreamsofcodeDreams of Code·1y

    There's more than one way to scale Redis/Valkey to 1M op/s...

    Exploring various strategies to scale Redis or Valkyrie to handle 1 million requests per second, including vertical scaling, horizontal scaling, pipelining, read replication, and using Redis cluster. The post discusses the challenges and benefits of each approach, and introduces Dragonfly DB as a high-performance alternative that can handle requests more efficiently without complex configurations.

See all Redis archives