Consistency over Availability: How rqlite Handles the CAP theorem

Summary

rqlite is a lightweight, user-friendly, open-source, distributed relational database. It’s written in Go and uses SQLite as its storage engine. When it comes to distributed systems the CAP theorem is an essential concept. It states that it’s impossible for a distributed database to simultaneously provide Consistency, Availability, and Partition tolerance. The challenge is in the face of a network partition, a database can only be available or consistent, but not both. Let’s take a look at the CAP theorem and see how rqlite fits into this fundamental trade-off. Understanding Consistency, Availability, and Partition Tolerance Consistency (C): A consistent system ensures that all nodes in a distributed cluster have the same data at the same time. This means any read request will return the most recently written data. Availability (A): An available system ensures that every request receives a response, regardless of network issues. The system continues to operate even if some nodes are unreachable, though there’s no guarantee the data will be the most recent. Partition tolerance (P): A partition-tolerant system continues to function even when network failures partition the system into isolated groups of nodes. When a network partition occurs, a choice must be made. Do you prioritize consistency by not responding to requests on the “bad” side of the partition, or do you prioritize availability by continuing to serve requests, even if it means potentially serving stale data? This is the core trade-off between CP and AP. CP vs. AP Systems A CP (Consistency-Partition tolerant) system prioritizes consistency. If a network partition occurs, the system will block writes on the minority side of the cluster to prevent data inconsistencies. This ensures that any data written is consistent, and when the partition is resolved, the system synchronizes without conflicts. An AP (Availability-Partition tolerant) system prioritizes availability. It continues to accept write requests on ...