This article shares hard‑learned production experience on using Spring Event, explaining why services must shut down gracefully before publishing events, how startup timing can cause event loss, which business scenarios fit the publish‑subscribe model, and practical reliability techniques such as retries and idempotency.
This guide explains Redis Pub/Sub as a communication pattern, shows what it can achieve, lists the most common commands with examples, demonstrates a multi‑client scenario, and outlines its drawbacks compared with newer Redis Streams.
This article provides Python code examples for using Redis as a database—including connection, basic CRUD, list and sorted set operations, key expiration, publishing/subscribing, distributed locking, and caching—followed by a detailed comparison of Redis and MySQL across data model, persistence, query capabilities, performance, scalability, and transaction support.
Learn how to use Redis with Python for basic CRUD, list and sorted‑set manipulation, key expiration, Pub/Sub messaging, distributed locks, and caching, and understand when Redis is a suitable complement or alternative to MySQL based on data model, performance, and transaction needs.
This article explains how Redis can be used to build message queues by leveraging List commands with LPUSH/RPOP and BRPOPLPUSH for simple queues, the Stream data type introduced in Redis 5.0 for durable, ordered, consumer‑group‑based queues, and the Pub/Sub model for real‑time broadcasting, while also analyzing the underlying source code structures such as quicklist, radix trees, and stream internals.
This article explains how Redis can be used to build lightweight, high‑performance message queues by leveraging lists for simple queues, sorted sets for delayed delivery, Pub/Sub for multicast, and the Stream data structure for durable, scalable messaging, while also covering practical PHP implementations, acknowledgment, retry, graceful restart, and rate‑limiting techniques.
This article provides a comprehensive guide to advanced Redis operations, covering pipeline usage, transaction handling, publish/subscribe mechanisms, key migration techniques, custom command implementation with Jedis, and efficient key scanning methods, complete with code examples and performance comparisons.
This article provides an in‑depth technical overview of Redis, covering its core data structures, memory allocation strategies, eviction policies, persistence mechanisms (RDB and AOF), transaction model, sentinel and cluster architectures, Pub/Sub messaging, and multiple approaches to implementing distributed locks.
Redis, a powerful in‑memory data store, offers versatile capabilities beyond simple key‑value storage, and this article explores five common real‑world scenarios—full‑page caching, leaderboards, session storage, queues, and pub/sub—demonstrating how to leverage its rich data structures for faster, more reliable applications.
Distributed queue programming treats a queue as a fundamental, cross‑process abstraction, guiding developers to select synchronous or asynchronous, decoupled, persistent messaging solutions and offering four core models—point‑to‑point, producer‑consumer, publish‑subscribe, and MVC—while the article illustrates real‑world designs for billing, cache updates, and ticket processing.
