> "Reliability: If one of your database servers is destroyed by a natural disaster, such as a typhoon or an earthquake, data is still preserved. You do not need to worry about data loss because data is replicated across multiple locations." **Source**: Alex Xu - *System Design Interview – An Insider's Guide* ## Context Data replication serves multiple purposes beyond disaster recovery: read scaling, reduced latency for geographically distributed users, and high availability. ## Replication Benefits | Benefit | Description | |---------|-------------| | **Reliability** | Data survives hardware/site failures | | **Availability** | System continues operating during failures | | **Read Scaling** | Distribute read load across replicas | | **Latency** | Place data closer to users | ## Replication Strategies - **Synchronous**: Write confirmed after all replicas updated (strong consistency, higher latency) - **Asynchronous**: Write confirmed after primary updated (lower latency, eventual consistency) - **Semi-synchronous**: Write confirmed after at least one replica updated (balance) ## Trade-offs More replicas = better durability but higher write latency and storage costs. ## Related Concepts - [[Database Replication]] - [[Eventual Consistency]] - [[Redundancy for Reliability]] ## Tags #system-design #data #replication #reliability