Relational Database High Availability and Replication Diagram

What this diagram shows

This diagram shows how a relational database maintains availability and consistency across multiple server nodes through synchronous or asynchronous replication. It depicts the primary database node handling write operations, one or more replica nodes receiving those changes, failover logic that redirects traffic if the primary fails, and monitoring systems that detect issues and trigger promotion of a replica to primary. The flow illustrates how client applications connect through a connection pool or load balancer, how transactions propagate to replicas, and how the system recovers when nodes become unavailable.

Key components

• Primary Database Node — Accepts all write and read operations from connected clients, generates transaction logs that feed replication streams.
• Replica Database Node — Receives and applies transaction logs from the primary in near real time, serves read-only queries to offload traffic.
• Replication Stream — Transmits transaction logs or binary logs from primary to replica continuously, using protocols like MySQL binlog streaming or PostgreSQL WAL shipping.
• Failover Manager — Monitors primary node health and automatically promotes a healthy replica to primary when the primary becomes unavailable or unresponsive.
• Virtual IP or DNS Name — Single connection endpoint for clients that automatically points to the current primary node after failover without requiring application reconfiguration.
• Connection Pool — Maintains persistent connections from application servers to the database and reroutes new connections after primary failure is detected.
• Monitoring and Health Check Agent — Polls primary and replica nodes at regular intervals to detect latency, CPU overload, or connection loss and signals the failover manager.

When to use it

Use this diagram when documenting database infrastructure for systems requiring high uptime and read scalability, such as SaaS platforms, financial applications, or e-commerce backends. It is essential for technical teams designing disaster recovery strategies, communicating redundancy architecture to stakeholders, or planning capacity around replication lag. This diagram works best when replication latency and consistency requirements are critical design constraints.

Common mistakes

• Showing replication as instantaneous synchronous across all nodes when actual systems have measurable replication lag that applications must account for.
• Omitting the monitoring and detection mechanism, suggesting failover happens magically rather than requiring explicit health checks and decision logic.
• Depicting multiple active primary nodes writing simultaneously without addressing conflicts, confusing multi-master replication with the single-primary topology.

Adapting it to your system

Identify your database engine and replication method: MySQL with binlog streaming, PostgreSQL with WAL archiving, or managed services like RDS with Multi-AZ. Replace generic node labels with actual instance names or server roles like 'Primary-us-east-1a' and 'Replica-us-east-1b'. Specify your failover tool: Patroni, MHA (MySQL High Availability), or cloud-native failover policies. Add connection path details specific to your network, such as HAProxy or application-level retries. Annotate replication lag expectations and recovery time objectives if these are design constraints.