🚀

Redis Overview and Use Cases

Sep 25, 2025

Overview

This lecture introduces Redis, explaining its roles as a cache, database, and message broker, and explores the technical reasons behind its speed and popularity.

What is Redis?

  • Redis stands for Remote Dictionary Server and is an open-source, in-memory data structure store.
  • It supports various data structures such as strings, hashes, lists, sets, sorted sets, and bitmaps.
  • Redis is commonly used as a caching layer to speed up data access by storing frequently used data in memory.

Redis Use Cases

  • As a cache, Redis reduces database load by storing and quickly retrieving frequently accessed data.
  • Redis can act as a primary database for applications needing real-time, low-latency data access, like gaming leaderboards.
  • As a message broker, Redis enables real-time communication using its publish/subscribe features, suitable for chat apps and notifications.

Reasons for Redis’s Speed

  • Redis stores all data in RAM (Random Access Memory), making reads and writes much faster than disk-based databases.
  • Accessing data in memory is much faster than from SSDs or HDDs.
  • Redis uses a key-value hash table for storage, allowing constant time (O(1)) lookups regardless of dataset size.
  • It operates using a single-threaded event loop, executing commands one at a time and avoiding complex locking.
  • Non-blocking IO lets Redis handle many client connections concurrently without waiting on input/output operations.
  • Redis uses simple, well-optimized data structures to minimize CPU usage and maximize speed.
  • Written in C, Redis benefits from efficient, low-level management of memory and CPU resources, enabling fine control for optimal performance.

Scalability and Limitations

  • Single-threaded design is efficient for memory operations but can limit performance for CPU-intensive tasks or very large datasets.
  • Redis can be scaled horizontally using Redis Cluster to partition data across multiple servers.
  • Redis modules can offload specific tasks to address heavy workloads.

Key Terms & Definitions

  • Cache — A temporary storage layer for frequently accessed data, speeding up retrieval.
  • In-memory database — A database that stores data in RAM for ultra-fast access.
  • Message broker — A system for passing messages between different parts of an application.
  • Publish/Subscribe (pub/sub) — A messaging pattern where publishers send messages to channels and subscribers receive messages from those channels.
  • Hash Table — A data structure mapping keys to values for efficient lookups.
  • O(1) time complexity — An operation whose duration is constant, regardless of dataset size.

Action Items / Next Steps

  • Watch the recommended video on distributed locking in Redis for deeper understanding.
  • Stay tuned for upcoming lessons on Redis data types and real-world applications.