About Database Replication Simulator

Simulate database replication scenarios with lag analysis and consistency checking. Part of the DevTools Surf developer suite. Browse more tools in the Developer Utilities collection.

Use Cases

• Understand how replication lag affects read replica query freshness
• Simulate failover scenarios before implementing high availability
• Design read/write routing strategies for replicated database setups
• Demonstrate eventual consistency implications to application developers

Tips

• Set the replication lag slider to simulate high-latency network conditions between primary and replica — observe which queries would return stale results
• Use the 'split brain' scenario to simulate what happens when network partition separates primary from replica and both accept writes
• Toggle consistency level (strong, eventual, monotonic) to see which query patterns are affected by each replication strategy

Fun Facts

• MySQL's binary log (binlog) replication, introduced in 1997, was the first widely used database replication system. It records every data modification as an event in a binary log file that replicas apply — a design still in use in MySQL and MariaDB today.
• The CAP theorem, proved by Eric Brewer in 2000, states that a distributed system can guarantee at most two of: Consistency, Availability, and Partition tolerance. During a network partition, a system must choose between consistency (refusing writes) or availability (allowing potentially inconsistent writes).
• Amazon Aurora's replication system synchronously replicates write operations to 6 copies across 3 Availability Zones before acknowledging a commit — but it only requires 4 of 6 writes to succeed. This design tolerates 2 simultaneous zone failures with zero data loss.

FAQ

What is the difference between synchronous and asynchronous replication?

Synchronous replication waits for at least one replica to confirm receipt before acknowledging a write — guaranteeing no data loss but adding latency. Asynchronous replication acknowledges immediately and replicates in the background — lower latency but potential data loss if the primary fails.

What causes replication lag and how do I reduce it?

Lag is caused by slow replica I/O, single-threaded SQL thread (MySQL < 5.6), large transactions, or network latency. Solutions: parallel replication (MySQL 8.0+, PostgreSQL), smaller transactions, dedicated replica hardware, and low-latency network between primary and replica.

Should application code be aware of replica lag?

For read-after-write consistency (reading your own writes immediately), always read from primary. For analytics and reporting queries that tolerate slightly stale data, replicas are appropriate. Session-level tracking of 'last write' position can route reads to a replica that is caught up to your write.