Strategies for READ Heavy Systems - rnakidi/dsa GitHub Wiki
There’s a 91.67% chance you’ll be working on a read-heavy system.
Read-heavy systems are the ones where the majority of requests involve fetching data from a database.
For example,
- Customers view dozens of products on Amazon before buying one.
- Users read hundreds of social media posts before posting one.
Here are 5 strategies that can help you build such systems:
✅ Perform Database Indexing Indexing your database tables is the absolute must-do activity for optimizing reads.
It allows the database to quickly locate the rows that match a given query.
✅ Database Replication (Read Replicas) Create read replicas of your database.
These replicas are copies of the primary database that can handle read requests.
With more replicas, you can distribute read requests and improve performance.
✅ Caching Caching is great for read-heavy systems where the data doesn’t change much after creation.
A good caching strategy can reduce the load on your database.
Look at caching solutions like Redis or Memcached for fast in-memory storage.
✅ Content Delivery Networks Take caching to the next level by investing in a CDN.
With a CDN, you can cache and serve static content closer to the end users and reduce read latency.
✅ Load Balancing You can spin up multiple replicas, cache instances, or servers to handle the reads.
But you also need to ensure fair distribution of traffic between these instances.
To do so, implement load balancing.