Database replication maintains copies of data across multiple servers. It improves availability and read throughput and protects against data loss, using single-leader, multi-leader, or leaderless models with different consistency tradeoffs.
Database replication - Interview Concepts - ExtraBrain is part of ExtraBrain's local-first Mac workflow for live interviews, meetings, transcription, provider control, and responsible AI use.
Database replication maintains copies of data across multiple servers. It improves availability and read throughput and protects against data loss, using single-leader, multi-leader, or leaderless models with different consistency tradeoffs.
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Writes go to a leader and replicate to followers that serve reads, the most common model.
Synchronous replication is durable but slower; asynchronous is faster but risks losing recent writes on failover.
Followers can trail the leader, so reads may be stale under eventual consistency.
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Replication copies the same data to many nodes; sharding splits different data across nodes. They are often combined.
The delay before a follower reflects a leader write, which can cause stale reads until it catches up.
