Distributed Database Replication 2026: PostgreSQL vs MySQL vs MongoDB Replication Comparison

Database replication is one of the most critical infrastructure decisions youll make. It determines whether your system can survive hardware failures, handle geographic distribution, scale reads, and meet compliance requirements. Yet many teams choose replication strategies without fully understanding the tradeoffs. This guide compares how the three most popular databases—PostgreSQL, MySQL, and MongoDB—handle replication.

What Is Database Replication?

Database replication copies data from a primary (source) database to one or more replicas (copies). This provides:

• High Availability: If primary fails, replica becomes primary (failover)
• Read Scaling: Distribute read-heavy queries across replicas
• Disaster Recovery: Keep data in multiple locations
• Compliance: Meet data residency requirements
• Backup: Use replicas as backup sources

PostgreSQL Replication

Primary Features

• Streaming Replication: WAL (Write-Ahead Log) shipping to replicas in real-time
• Synchronous/Asynchronous: Choose consistency vs latency tradeoff
• Multi-replica: Replicate to unlimited replicas
• Cascade replication: Replica can replicate to another replica
• Logical replication: Selective replication of specific tables/schemas

Implementation Complexity

Streaming Replication: Moderate (PostgreSQL handles automatic WAL shipping)

Failover: Manual or via pg_basebackup (requires tooling for automation)

Tools: pg_basebackup, WAL archiving, replication slots

Replication Lag

• Asynchronous: <100ms typical
• Synchronous: 10-50ms typical

Operational Overhead

Medium. Need to:

• Configure replication slots
• Monitor WAL archiving
• Set up automated failover (if needed)
• Manage backup strategies

Best For

PostgreSQL shops needing: read scaling, HA, disaster recovery, geographic distribution

MySQL Replication

Primary Features

• Binlog-based: Binary log contains all database changes
• Master-Slave: One master, multiple slaves (standard setup)
• Semi-synchronous: Balance between performance and consistency
• Multi-source replication: Replica can replicate from multiple masters
• Row vs Statement: Choose replication granularity
• GTID: Global Transaction IDs for easier failover

Implementation Complexity

Standard replication: Simple (set replication user, provide master details)

Failover: More complex than PostgreSQL (requires MySQL Router or MHA)

Tools: mysqldump, binlog, MySQL Router, Percona XtraBackup

Replication Lag

• Async: <100ms typical
• Semi-sync: 10-100ms typical (variable)

Operational Overhead

Medium to High. Need to:

Best For

MySQL shops with read-heavy workloads, geographic distribution, those comfortable with operational complexity

MongoDB Replication

Primary Features

• Replica Sets: 3+ nodes in cluster (not traditional master-slave)
• Automatic Failover: If primary fails, secondary elected automatically
• Read Preferences: Route reads to primary, secondaries, or nearest node
• Oplog: Operations log enables replication and recovery
• Sharding: Combine replication with sharding for scale
• Journaling: All writes journaled before applied (durability)

Implementation Complexity

Replica Set: Simple (initiate replica set with 3+ nodes)

Failover: Automatic (no tooling needed)

Tools: mongod (built-in), MongoDB Ops Manager (optional)

Replication Lag

• Async: <1000ms typical (can be higher)
• Acknowledged writes: Durability confirmed after primary write

Operational Overhead

Low. MongoDB handles most operations automatically. Need to:

• Monitor replica set health
• Plan for majority node locations (quorum)
• Configure oplog size

Best For

MongoDB shops, applications needing automatic failover, document-based systems, cloud-native architectures

Detailed Comparison

Real-World Setup Scenarios

PostgreSQL: High-Availability Setup

Primary: PostgreSQL server (receive writes, replicate to standbys)
Standby 1: PostgreSQL replica (ready for failover)
Standby 2: PostgreSQL replica (geographic redundancy)
Tools: pg_basebackup for initial setup, WAL archiving for durability
Failover: Manual promotion or pg_auto_failover for automation

MySQL: Multi-Region Setup

Master (US-East): MySQL server (receive writes)
Slave1 (US-West): MySQL replica (regional failover)
Slave2 (EU): MySQL replica (disaster recovery)
Tools: mysqldump for backup, MySQL Router for read distribution
Failover: Manual or MHA (Percona Master High Availability)

MongoDB: Replica Set Setup

Primary: MongoDB node (receives all writes)
Secondary1: MongoDB node (auto-failover candidate)
Secondary2: MongoDB node (geographic distribution)
Features: Automatic primary election if primary fails
Failover: Automatic (no tools needed)

Choosing Replication Strategy

Choose PostgreSQL if

• You need strong ACID guarantees
• You want synchronous replication option
• Youre comfortable with manual failover setup
• You need logical replication flexibility

Choose MySQL if

• You have existing MySQL infrastructure
• You need semi-synchronous replication
• Youre willing to invest in failover tooling (MHA, MySQL Router)
• You need multi-source replication

Choose MongoDB if

• You value automatic failover above all
• Youre using document-based data model
• You want simplest operational model
• Youre building cloud-native applications

Final Recommendation

For HA + read scaling: PostgreSQL (streaming replication) or MongoDB (replica sets)

For minimum operational overhead: MongoDB (automatic failover)

For maximum control: PostgreSQL (synchronous replication option)

The database you choose should drive replication strategy, not vice versa.