Cache Systems Every Developer Should Know

Data is cached everywhere, from the client-facing side to backend systems. Let’s look at the many caching layers:

Caching Layers

1. Client Apps: Browsers cache HTTP responses. Server responses include caching directives in headers. Upon subsequent requests, browsers may serve cached data if still fresh.

2. Content Delivery Networks: CDNs cache static content like images, stylesheets, and JavaScript files. They serve cached content from locations closer to users, reducing latency and load times.

3. Load Balancers: Some load balancers cache frequently requested data. This allows serving responses without engaging backend servers, reducing load and response times.

4. Message Brokers: Systems like Kafka can cache messages on disk per a retention policy. Consumers then pull messages according to their own schedule.

5. Services: Individual services often employ caching to improve data retrieval speeds, first checking in-memory caches before querying databases. Services may also utilize disk caching for larger datasets.

6. Distributed Caches: Systems like Redis cache key-value pairs across services, providing faster read/write capabilities compared to traditional databases.

7. Full-text Search Engines: Platforms like Elasticsearch index data for efficient text search. This index is effectively a form of cache, optimized for quick text search retrieval.

8. Databases: There are specialized mechanisms to enhance performance, some of which include caching concepts:

Database Caching Mechanisms

• Bufferpool: This is a cache within the database that holds copies of data pages. It allows for quick reads and writes to temporary storage in memory, reducing the need to access data from disk.

• Materialized Views: They are similar to caches in that they store the results of computationally expensive queries. The database can return these precomputed results quickly, rather than recalculating them.