Multi-master architecture has gained significant traction in the world of database management, offering a solution to traditional limitations in scalability, fault tolerance, and high availability. By allowing multiple nodes to operate as master, this architecture promises a more flexible and robust database system. However, along with these benefits come certain challenges, including data consistency, resource demands, and conflict resolution.

In this blog, we will explore what multi-master architecture is, delve into its key advantages, and discuss the potential drawbacks that come with its implementation. Also in our upcoming blogs, we will see how you can setup your first multi-master architecture with a tool called PGD (Postgres Distributed) by EnterpriseDB (EDB).

What is Multi-Master architecture?

Multi-master architecture is a database design approach where multiple nodes, or database servers, act as masters, each capable of accepting read and write operations same time. In multi-master systems, data changes on one node are propagated to the other nodes to maintain consistency across the cluster.

Source: e2enetworks

As illustrated in the diagram, a user can read and write data on any of the three available nodes, and the data is replicated among all the nodes, ensuring that each node has a consistent copy of the data.

NOTE: Standard PostgreSQL doesn’t support bi-directional replication, but starting from PostgreSQL 16, you can use bi-directional replication if all nodes in the setup are publishers and subscribers at the same time. However, be aware that DDL commands and sequences are still not supported.

Prons for using Multi-Master architecture

High Availability

With multi-master architecture, our system can continue functioning even if one or more nodes fail. Since multiple nodes can act as masters, there’s no single point of failure.

Improved Read and Write Scalability

Multi-master setups allow concurrent reads and writes across different nodes, enabling you to distribute the load more evenly. This can significantly improve performance, especially in high-traffic environments.

Geographical Distribution

Multi-master architecture allows you to have nodes in different geographical locations. This can reduce latency for users in various regions and improve disaster recovery capabilities.

Load Balancing

With multiple masters, you can implement load-balancing strategies to distribute traffic among nodes, reducing bottlenecks and improving performance.

Flexible Maintenance

Maintenance tasks can be performed on individual nodes without affecting the entire system. You can take a node offline for maintenance while others continue to serve requests.

Simplified Scaling

Scaling is easier with multi-master architecture. You can add new nodes to the cluster to increase capacity, allowing you to scale horizontally as your workload grows.

Distributed Data Processing

With multiple masters, you can distribute data processing tasks across nodes, allowing for parallel processing and reducing the time required for complex operations or large-scale data analyses.

Cons for Multi-Master architecture

Data Consistency Challenges

With multiple masters, ensuring data consistency can be challenging. Write operations occurring simultaneously on different nodes can lead to data conflicts, and resolving these conflicts often requires robust mechanisms. This is where tools like PGD come into play we will cover this in our next parts.

Increased Latency Due to Replication

In a multi-master architecture, changes made to one node must be replicated to other nodes to maintain consistency. This replication process can introduce latency, especially if the nodes are geographically distributed.

Higher Resource Consumption

Maintaining multiple master nodes with bidirectional replication can consume more resources, including CPU, memory, and network bandwidth. This can lead to higher operational costs compared to a single-master setup.

Difficulties with Consistent Backups

Creating consistent backups in a multi-master environment is more complex, as data is being modified across multiple nodes. This complexity can complicate disaster recovery and data restoration processes. Again a positive feature of PGD.

Risk of Split-Brain Scenarios

In multi-master systems, network partitions or communication issues can lead to split-brain scenarios where two or more nodes operate independently, causing data divergence and other issues.

Increased Configuration and Management Overhead

Multi-master setups require more complex configurations and ongoing management to ensure proper operation. This includes setting up replication, handling conflicts, monitoring nodes, and maintaining system health.

Licensing and Cost Considerations

Multi-master configurations may require additional software, extensions, or third-party tools to manage replication and conflict resolution, potentially increasing licensing and operational costs.

NOTE: The majority of the drawbacks listed above are already addressed by PGD, so there’s no need to worry about setting things up, managing backups, or manually re-attaching failed nodes to the cluster. PGD handles these tasks for us.

Further Reading: AI Meets PostgreSQL – The pgvector Revolution in Text Search

When to Use Traditional Primary-Standby

Consider Primary-Standby architecture if you answer yes to these questions:

Consistency: Do I need strong consistency with all writes occurring on a single node?
Infrastructure Complexity: Am I looking for a simpler setup with fewer complexities in replication and conflict resolution?
Maintenance and Failover: Can I manage manual failover and maintenance?

When to Use Multi-Master

Consider Multi-Master architecture if you answer yes to these questions:

Fault Tolerance: Is high availability crucial, with automatic failover and no single point of failure?
Scalability: Do I need to scale with concurrent writes from multiple sources or geographic locations?
Infrastructure Complexity: Am I willing to manage more complex systems with advanced replication and conflict resolution mechanisms?
Maintenance and Failover: Do I prefer automated failover with minimal manual intervention for maintenance?
License Cost: Am I ready to bear the licensing costs for the tool we plan to use to implement this setup?

Real-world use cases of Multi-Master architecture

E-commerce with geographically distributed warehouses: Enable real-time inventory updates across warehouses for accurate order fulfillment.
Global financial institutions: Facilitate high availability and geographically dispersed access to financial data.
Online gaming platforms: Ensure continuous gameplay and data consistency across geographically distributed servers.
Telecommunications Networks: Multi-master setups support the high-availability needs of telecom networks, enabling multiple nodes to manage customer data and maintain consistent information during peak loads.

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