Introduction
Caching is a powerful technique to speed up data retrieval and improve system latency by storing frequently accessed data in memory.
What is Caching?
Caching is a way to store data for a short time in a place that's easy to access. By keeping data nearby, caching makes it faster to get data from slower storage areas. This speeds up response times for user requests.
Where is Caching Applied?
Caching can be implemented at various levels, including:
Client-side: Where data like images, CSS, and JavaScript files are stored on the user’s browser to reduce redundant network requests.
Server-side: Where results from frequent database queries are stored to avoid repeated database calls, thereby reducing server response times.
Database level: Where frequently accessed data is cached to expedite query processing.
Use Cases of Caching
Caching proves most beneficial in scenarios where:
A client makes repetitive requests to a server.
A server frequently accesses data from a database.
Static files that don’t change often need to be quickly available to users.
Write Through vs. Write Back Cache
These are two popular ways of writing to cache.
Write Through Cache
In this approach, data is written to both the cache and the database simultaneously, ensuring consistency between the two.
The main advantage is the assurance that data remains synchronized.
However, this can lead to slower write operations since data must be written to the slower database as well.
Write Back Cache
On the other hand, write back caching writes data only to the cache initially, with the cache later responsible for writing to the database.
This method offers faster write speeds and reduces the load on the database.
The risk, though, is potential data loss if the cache fails before it writes back to the database.
Managing Consistency
Caching can introduce consistency challenges, especially in systems where data is updated frequently.
Strategies to maintain consistency include setting expiration times for cached data or using more complex invalidation schemes to ensure cached data reflects the current state of the database.
General Caching Strategies
To maximize the effectiveness of caching, consider the following principles:
Cache data that changes infrequently.
Cache data that is frequently accessed.
Cache computationally expensive data.
Cache data that is geographically distant from its requesters.
Cache large data items to reduce data transfer times.
Cache Eviction Policies
When the cache reaches its capacity, older or less frequently accessed data must be evicted (removed) to make room for new entries.
The most common eviction strategy is the Least Recently Used (LRU) method, which removes the items that haven't been accessed for the longest time.
Conclusion
Caching is a key part of system design for better performance, shorter delays, and managing backend system loads. By using caching smartly and choosing the right removal policies, you can enhance the user experience and possibly save money.
