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What is the difference between database failover and replication?
| Term | What it does | What it does not guarantee |
|---|---|---|
| Replication | Copies database changes from a primary to one or more secondary systems. | Automatic promotion, zero data loss, or continuous availability. |
| Failover | Changes which database system serves as primary after an outage, usually by promoting a standby or replica. | An instant recovery or a particular recovery time and data-loss outcome. |
A standby may be kept ready but unavailable to clients until it is promoted, or it may be allowed to serve read-only queries. The exact behavior depends on the database and configuration. PostgreSQL describes replication and standby arrangements in its high-availability documentation.
Does replication automatically fail over?
No. Replication maintains a copy or stream of changes; failover requires a mechanism to detect a failure, decide that promotion is appropriate, promote the standby, route clients to it, and reconnect workloads. Some high-availability setups automate these actions. A disaster-recovery replica may instead require an operator to promote it deliberately.
For example, Google Cloud SQL’s cross-region PostgreSQL replica guidance describes promotion as manual and intentional for regional migration or disaster recovery. It distinguishes this from high availability, where a standby can become primary automatically after a failure or zonal outage. These are provider-specific behaviors, not universal database rules.
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How replication mode affects data loss and write latency
Asynchronous replication
The primary does not wait for a replica to confirm each write before acknowledging it. This avoids the acknowledgement delay, but the replica can lag. If the primary fails, recently committed transactions that have not reached the replica may be missing from the promoted system. The risk depends on replication delay and the failure.
In PostgreSQL, streaming replication is asynchronous by default. Its standby documentation says that committed transactions not yet replicated can be lost after a primary crash, with the amount of potential loss proportional to replication delay. Google Cloud SQL also documents asynchronous cross-region replication, so writes not yet replicated may be lost in a regional outage.
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Synchronous replication
With synchronous replication, a commit waits for confirmation from a standby under the configured rules. This can improve protection against losing acknowledged writes, but adds latency—especially when the systems communicate over a long network distance. It is not a universal guarantee of zero data loss in every design; the acknowledgement and durability settings matter.
For PostgreSQL specifically, synchronous commits wait for confirmation that the commit record has been written to durable storage on the primary and standby. PostgreSQL notes that this raises transaction response time by at least the round-trip time between them. Its PostgreSQL 17 high-availability documentation explains the trade-off: “Asynchronous communication is used when synchronous would be too slow.” PostgreSQL 17: High Availability, Load Balancing, and Replication.
Why failover does not mean zero downtime
Failover is a sequence of recovery steps, not an instant synonym for uninterrupted service. Time can be spent detecting the failure, recovering the standby, promoting it, updating routing or DNS, and waiting for applications to reconnect. Applications may also need retry behavior that handles dropped connections and in-flight requests safely.
Azure Database for PostgreSQL Flexible Server documents a provider-specific example: its standby remains in recovery until promotion and cannot serve read queries while acting as the high-availability standby. Azure says monitoring can initiate automatic failover and DNS is updated so the existing endpoint points to the new primary. Its current documentation, checked in 2026, says zone-redundant recovery is typically 60–120 seconds with zero data loss, while warning that workload-dependent recovery can take longer than 120 seconds. Those figures apply to the described Azure configuration, not databases generally. See Azure’s high-availability documentation.
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Replication is not a substitute for backups
A replica can reproduce unwanted changes as well as wanted ones. If someone drops a table or writes incorrect data, replication may copy that change to the standby. Replication primarily supports availability or disaster recovery; it does not necessarily preserve a clean historical copy. Azure recommends point-in-time restore for logical mistakes such as accidental deletion or bad writes. Choose and test backups and restore procedures separately.
How to choose a design for your recovery needs
Start with explicit recovery objectives, then check whether the database design and operating procedures can meet them. Google Cloud’s high-availability architecture guidance frames the choice around service objectives and tolerance for downtime and data loss.
| Decision factor | Question to answer |
|---|---|
| Recovery time objective (RTO) | How long can the service be unavailable while detection, recovery, promotion, routing, and client reconnection happen? |
| Recovery point objective (RPO) | How much missing or lost data can the business tolerate, and could acknowledged commits be absent from the promoted server? |
| Failure scope | Must the design cover a database node or zone failure, a regional outage, or more than one of these? |
| Promotion and operations | Will failover be automatic or manual? How will you prevent split brain, monitor lag, test promotion, and reconfigure the former primary? |
| Read capacity | Can the secondary serve read-only queries, or is it reserved for promotion? |
| Latency and distance | Can write workloads tolerate synchronous acknowledgement delays, including network round trips between regions? |
| Cost | What extra compute, storage, data transfer, and managed-service charges will the chosen deployment add? |
A practical design specifies the failure it is meant to cover, the acceptable RTO and RPO, the promotion decision, and how applications find and reconnect to the active primary. It also tests recovery rather than assuming that a healthy-looking replica will be ready under real outage conditions.
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