Replication keeps another database copy updated; failover switches database service to that copy when the primary is unavailable. Replication can support failover, but it does not by itself provide automatic promotion, zero data loss, or uninterrupted service. Those outcomes depend on replication mode and lag, failure scope, promotion and routing behavior, and how quickly clients reconnect.
What is the difference between database failover and replication?
Replication is the process of sending database changes from a primary system to one or more secondary systems. Failover is the change in role that makes a standby or replica serve as the primary after an outage. In short, replication maintains a copy; failover changes which system handles service. A secondary may be kept ready but unavailable to clients, or it may be able to serve read-only queries. PostgreSQL describes these high-availability roles in its high-availability documentation.
A replicated database may be used for read scaling, migration, disaster recovery, or high availability. The setup determines which of those it can actually support. In particular, a replica intended for disaster recovery may need a person to promote it, while a high-availability standby may be promoted automatically under configured failure conditions.
Does replication automatically fail over?
No. Replication moves or records changes; a separate mechanism must detect a failure, decide whether promotion is safe, promote the standby, direct clients to it, and restore application connections. The process can be automatic or manual. For example, Google Cloud SQL documents cross-region PostgreSQL replica promotion as a manual, intentional action for migration or disaster recovery, distinct from its high-availability standby behavior, where a standby can become primary after a failure or zonal outage. See Cloud SQL cross-region replica guidance.
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“Automatic” also does not mean instantaneous or invisible to an application. Detection, recovery, promotion, endpoint updates, and client retries all affect the outage. In Azure Database for PostgreSQL Flexible Server, the standby remains in recovery until promotion; Azure documents monitoring-initiated automatic failover and DNS updates that direct the existing endpoint to the new primary. Azure says zone-redundant recovery is typically 60–120 seconds with zero data loss for that service configuration, but workload-dependent recovery can take longer than 120 seconds. These are Azure-specific documented figures, not general database guarantees. Azure’s high-availability documentation describes the behavior.
How do synchronous and asynchronous replication affect data loss and latency?
With asynchronous replication, the primary can acknowledge a commit before a secondary has received it. This avoids waiting for the secondary on each commit, but a failure can leave recent committed transactions missing on the replica selected for promotion. The risk depends on replication delay at the time of failure. PostgreSQL streaming replication is asynchronous by default; its standby documentation says transactions not yet replicated when the primary crashes may be lost, with the amount tied to replication delay. PostgreSQL’s standby documentation explains the implementation-specific behavior.
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With synchronous replication, a commit waits for acknowledgement from a configured standby, improving protection against losing acknowledged writes if that standby is then promoted. The cost is additional write latency: the primary must wait for the standby, including network communication. PostgreSQL documents that synchronous commits wait for the configured servers to commit and that response time increases by at least the round-trip time between primary and standby. These details describe PostgreSQL behavior, not a universal rule for every database.
PostgreSQL’s Global Development Group summarizes the trade-off in its PostgreSQL 17 high-availability documentation: “Asynchronous communication is used when synchronous would be too slow.” The practical choice is not simply “safe” versus “fast”: it is a decision about tolerated data loss, commit latency, replica location, and how the system behaves during a failure.
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How should you compare failover designs?
Set recovery objectives before choosing a topology. Recovery time objective (RTO) is the acceptable time for service to resume; recovery point objective (RPO) is the acceptable amount of recent data that could be lost. Both depend on business requirements and the failure being addressed. Google Cloud’s architecture guidance recommends choosing an architecture against service objectives and tolerance for downtime and data loss. Google Cloud’s PostgreSQL high-availability guidance also notes the cost of additional infrastructure and storage.
| Design concern | Question to answer |
|---|---|
| Recovery time (RTO) | How long can detection, recovery, promotion, endpoint routing, and client reconnection take? |
| Recovery point (RPO) | Can acknowledged commits be absent from the promoted server? What replication mode and lag apply? |
| Promotion | Does health monitoring trigger automatic failover, or must an operator intentionally promote the replica? |
| Failure scope | Does the design cover a database node, an availability zone, or a regional outage? |
| Read capacity | Can the secondary handle read-only queries, or is it reserved for recovery and promotion? |
| Write latency | Does synchronous acknowledgement add a network wait, and how far apart are the primary and standby? |
| Operations | How will you prevent split brain, monitor replication lag, test recovery, and reconfigure after promotion? |
| Cost | What extra compute, storage, data transfer, and managed-service charges apply to this deployment? |
Local high availability and cross-region disaster recovery address different failure scopes. A nearby standby may support faster recovery from a node or zone problem, while a cross-region replica is intended to help when the primary region is unavailable. The latter can involve longer network distances and asynchronous replication. Google Cloud SQL specifically documents asynchronous cross-region PostgreSQL replication, so primary-region failure can leave some unreplicated writes unavailable after promotion.
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Is a replica the same as a backup?
No. Replication is not a substitute for a recoverable backup. A dropped table or incorrectly written data can be replicated to the secondary along with valid changes. Azure recommends point-in-time restore for these logical mistakes rather than relying on its high-availability standby. A replica helps maintain another system, while a backup provides a recovery path to an earlier state.
What does a replica actually guarantee?
Nothing beyond the behavior of its specific configuration. A replica may be behind the primary, may not accept client traffic, may require manual promotion, or may cover only a particular failure scope. PostgreSQL documents asynchronous streaming as its default and describes synchronous alternatives; Google Cloud SQL distinguishes manually promoted cross-region replicas from automatic HA behavior; Azure describes a provider-specific synchronous HA arrangement whose standby cannot serve read queries while it is acting as the HA standby. Check the database or provider documentation for the exact deployment rather than treating “replicated” or “high availability” as a universal promise.
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