Key-value stores are the simplest form of NoSQL databases, yet they power some of the most sophisticated systems on the internet. From caching to session storage to distributed coordination, understanding how to design a key-value store is fundamental to system design.
This isn’t just a theoretical exercise—designing a key-value store is a popular system design interview question because it touches on so many important concepts: hashing, partitioning, replication, consistency, and more.
What You’ll Learn
In this section, we’ll walk through designing a distributed key-value store from scratch:
- Requirements: Functional and non-functional requirements
- API design: Simple operations (get, put, delete) with complex implications
- Data partitioning: Distributing data across multiple nodes
- Replication: Ensuring data durability and availability
- Consistency models: Strong consistency vs eventual consistency
- Failure handling: What happens when nodes crash
- Optimisations: Bloom filters, compaction, and more
Why This Matters
Key-value stores like Redis, DynamoDB, and Memcached are everywhere:
- Redis powers caching for millions of applications
- DynamoDB handles massive scale for AWS customers
- Memcached speeds up database queries across the web
Understanding how they work internally will help you:
- Choose the right key-value store for your needs
- Design better data models
- Debug performance issues
- Ace the “design a key-value store” interview question
From Simple to Sophisticated
We’ll start with a simple in-memory hash map and gradually add features to handle distribution, failures, and scale. By the end, you’ll understand how companies like Amazon built DynamoDB and why it works the way it does.
Ready to build your own key-value store? Let’s start!