Types of Caching

Caching is a technique used to store copies of data or resources temporarily in a high-speed storage layer (e.g., memory) to reduce latency, improve performance, and decrease the load on primary data sources (e.g., databases, APIs). Caching is a critical component of system design, especially for scalable and high-performance applications. Below are the types of caching commonly used in system design:

1️⃣ Client-Side Caching

Caching done on the client side (e.g., browser, mobile app) to store data locally and avoid repeated requests to the server.

Use Cases:

• Storing static assets like images, CSS, and JavaScript files.
• Caching API responses for faster access.

Examples:

• Browser Caching: HTTP headers like Cache-Control and Expires are used to control how long resources are cached in the browser.
• Mobile App Caching: Storing frequently accessed data (e.g., user profiles, settings) locally on the device.

Advantages:

• Reduces server load.
• Improves user experience by reducing latency.

Disadvantages:

• Limited storage capacity on the client side.
• Stale data issues if the cache is not invalidated properly.

2️⃣ Server-Side Caching

Caching done on the server side to store data that is frequently accessed  by clients.

Use Cases:

• Caching database query results.
• Storing session data or frequently accessed API responses.

Examples:

• In-Memory Caching: Using tools like Redis or Memcached to store key-value pairs in memory.
• Application-Level Caching: Frameworks like Django or Spring provide built-in caching mechanisms.

Advantages:

• Reduces database load.
• Improves response times for repeated requests.

Disadvantages:

• Requires memory resources on the server.
• Cache invalidation can be complex.

3️⃣ Distributed Caching

Definition: A caching system where the cache is distributed across multiple servers or nodes, often used in large-scale applications.

Use Cases:

• Scaling applications across multiple servers.
• Sharing cached data across different services in a microservices architecture.

Examples:

• Redis Cluster: A distributed version of Redis that allows horizontal scaling.
• Memcached: A distributed memory caching system.

Advantages:

• High availability and fault tolerance.
• Scalable to handle large amounts of data.

Disadvantages:

• Increased complexity in managing the distributed system.
• Network latency between cache nodes.

4️⃣ CDN Caching (Content Delivery Network)

Definition: Caching static content (e.g., images, videos, CSS, JavaScript) on geographically distributed servers to reduce latency for users.

Use Cases:

• Delivering static assets for websites and applications.
• Streaming videos and large files.

Examples:

Cloudflare, Akamai, AWS CloudFront: Popular CDN providers.

Advantages:

• Reduces latency by serving content from the nearest edge server.
• Offloads traffic from the origin server.

Disadvantages:

• Limited to static content.
• Cost increases with high traffic.

5️⃣ Database Caching

Definition: Caching frequently accessed database queries or results to reduce the load on the database.

Use Cases:

• Caching the results of expensive or repetitive queries.
• Storing precomputed data for faster access.

Examples:

• Query Caching: MySQL query cache (deprecated in newer versions).
• Materialized Views: Precomputed views stored in the database.

Advantages:

• Reduces database load and improves query performance.
• Simplifies complex queries by caching their results.

Disadvantages:

• Stale data issues if the underlying data changes.
• Requires careful cache invalidation.