Redis Bloom Filters: Designing a Memory-Efficient checking system

Problem Statement:

Many applications require ensuring the uniqueness of user-provided fields, such as usernames. This is a common requirement for web applications, where usernames should be unique for each registered user. While on a small scale, you can achieve this by querying the database and enforcing unique constraints, this approach becomes challenging as the registration rate increases. In this article, we will explore how to design a system that can efficiently handle uniqueness verification at scale using Redis Bloom filters.

Database-Backed Uniqueness Check:

On a small scale, you can perform a database query to check if a username is already in use. However, as the registration rate increases, this approach may not scale efficiently. To address this, you can introduce a Redis cache. By maintaining a Redis set containing all usernames, you can significantly speed up queries. When a request comes in to verify a username, you only need to check the cache, eliminating the need to hit the database. However, this method requires substantial memory, particularly if you have a large number of records.