High‑Availability Clustering Solutions for PostgreSQL

If your system depends on a PostgreSQL database and you are looking for a high‑availability (HA) clustering solution, be aware that it is a complex task but not impossible.

We will discuss several solutions from which you can choose according to your fault‑tolerance requirements.

PostgreSQL itself does not support any multi‑master clustering solution like MySQL or Oracle. Nevertheless, many commercial and community products provide such implementations, as well as other products such as PostgreSQL replication or load balancing.

What Is High Availability?

It is the amount of time a service remains available, usually defined by the enterprise.

Redundancy is the foundation of high availability; in case of an incident we can continue operating without problems.

Continuous Recovery

If an event occurs, you must restore a backup and then apply WAL logs; recovery time will be very long, and we would not call it high availability.

However, if we store backups and logs on a standby server, we can apply them when the logs arrive.

If logs are sent and applied every minute, the standby will be in a continuous recovery state, and the time to production will be at most one minute.

Standby Database

The idea of a standby database is to keep a copy of the production database that always has the same data and can be used when an event occurs.

There are several ways to classify standby databases:

By the nature of replication:

Physical standby: replicates disk blocks.

Logical standby: streams data changes.

By transaction synchrony:

Asynchronous: data loss possible.

Synchronous: no data loss; commits on the primary wait for a response from the standby.

By usage:

Hot standby: does not support connections.

Warm standby: supports read‑only connections.

Cluster

A cluster is a group of hosts working together and seen as a single host.

This provides a way to achieve horizontal scalability and the ability to handle more work by adding servers.

It can tolerate node failures and continue operating transparently.

Based on shared content, there are two models:

Shared storage: all nodes use the same information to access the same storage.

Non‑shared: each node has its own storage; depending on system architecture, the storage may contain the same information as other nodes.

Now let’s review some PostgreSQL clustering options.

Distributed Replicated Block Device (DRBD)

DRBD is a Linux kernel module that provides synchronous block replication over the network. It does not implement clustering itself nor handle failover or monitoring; you need complementary software such as Corosync + Pacemaker + DRBD.

Example components:

Corosync: handles messaging between hosts.

Pacemaker: starts and stops services, ensuring they run on only one host.

DRBD: synchronizes data at the block‑device level.

ClusterControl

ClusterControl is an agent‑less management and automation software for database clusters. It helps deploy, monitor, manage, and scale database servers/clusters directly from its UI.

ClusterControl can handle most management tasks required for maintaining database servers or clusters.

Using ClusterControl you can:

Deploy standalone, replicated, or clustered databases on your chosen technology stack.

Automate failover, recovery, and routine tasks across multi‑language databases and dynamic infrastructure.

Create full or incremental backups and schedule them.

Perform unified, comprehensive real‑time monitoring of the entire database and server infrastructure.

Add or remove nodes with a single operation.

In PostgreSQL, if an event occurs, it can automatically promote a replica to primary.

It is a very complete tool with a free community edition (including a free enterprise trial).

Rubyrep

An asynchronous, multi‑master, multi‑platform replication solution (implemented in Ruby or JRuby) that works with MySQL or PostgreSQL.

It is trigger‑based, does not support DDL, users, or privileges.

Simplicity of use and management is its main goal.

Simple configuration.

Easy installation.

Platform‑independent, table‑design independent.

Pgpool‑II

Pgpool‑II is middleware that sits between PostgreSQL servers and PostgreSQL clients.

Key features include:

Connection pooling.

Replication.

Load balancing.

Automatic failover.

Parallel query.

Bucardo

Row‑based asynchronous cascading master‑slave replication using triggers to queue changes; also supports row‑based asynchronous multi‑master replication with custom conflict resolution.

Bucardo requires a dedicated database and runs as a Perl daemon that communicates with that database and all other databases involved in replication. It can operate as multi‑master or multi‑slave.

Source databases must be PostgreSQL; targets can be PostgreSQL, MySQL, Redis, Oracle, MariaDB, SQLite, or MongoDB.

Features:

Load balancing.

Unlimited slaves that can also write.

Partial replication.

On‑demand replication (changes can be pushed automatically or when needed).

Slaves can be “pre‑warmed” for fast setup.

Drawbacks:

Cannot handle DDL.

Cannot handle large objects.

No unique key means incremental replication of tables is impossible.

Not suitable for PostgreSQL versions prior to 8.

Postgres‑XC

Postgres‑XC is an open‑source project that aims to provide a writable, scalable, synchronous, symmetric, and transparent PostgreSQL clustering solution. It is a tightly coupled collection of database components that can be installed on multiple physical or virtual machines.

Writable scalability means you can configure any number of database servers and handle more write operations than a single server.

Multiple client connections see a single consistent view of the cluster.

Any update on any server is immediately visible to transactions on other servers.

Transparency means you do not need to worry about how data is stored across multiple servers.

Data can be distributed by partitioning or replication, and queries are routed to the appropriate node.

Citus

Citus replaces PostgreSQL with built‑in HA features such as automatic sharding and replication. It shards your database and replicates each shard across multiple nodes; if any node fails, Citus transparently redirects writes or queries to another node that holds a replica of the affected shard.

Features include:

Automatic logical sharding.

Built‑in replication.

Data‑center‑aware replication for disaster recovery.

Mid‑query fault tolerance with advanced load‑balancing.

It helps increase uptime of real‑time applications supported by PostgreSQL and minimizes the impact of hardware failures.

PostgresXL

PostgresXL is a shared‑nothing, multi‑master clustering solution that transparently distributes tables across a set of nodes and executes queries in parallel. It includes a Global Transaction Manager (GTM) that provides a global consistent view of the cluster.

It is based on PostgreSQL 9.5 and is supported commercially by companies such as 2ndQuadrant.

PostgresXL can handle a wide range of workloads, including OLTP write‑intensive, MPP BI, operational data stores, key‑value, GIS, mixed workloads, and multi‑tenant environments.

Components:

Global Transaction Manager (GTM): ensures transaction consistency across the cluster.

Coordinator: manages user sessions and interacts with GTM and data nodes.

Data nodes: store the actual data.

Conclusion

Many other products can create a high‑availability environment for PostgreSQL, but you must watch out for new, untested products, discontinued projects, limitations, licensing costs, complex implementations, and insecure solutions.

You also need to consider your infrastructure; if you have only one application server, HA for the database alone will not help if the application server fails. Analyze single points of failure in your architecture and try to mitigate them.

By keeping these points in mind, you can find a solution that fits your needs without trouble and successfully implement a high‑availability PostgreSQL cluster. Good luck!