Administration guide > Plan the WebSphere eXtreme Scale environment > Cache topology

Multi-master data grid replication topologies

Use the multi-master asynchronous replication feature, two or more data grids can become exact mirrors of one other. This mirroring is accomplished using asynchronous replication among links connecting the data grids together. Each data grid is hosted in an independent catalog service domain, with its own catalog service, container servers, and a unique name. With the multi-master asynchronous replication feature, you can use links to interconnect a collection of these catalog service domains. Then, you can synchronize the catalog service domains with replication over the links. You can construct almost any topology because you choose how to define links among catalog service domains.

[v7.1 and later] Multi-master data grid replication is a significant new feature in v7.1. The feature is also called AP (availability and partitioning) replication in the context of the CAP theorem. The CAP theorem states that a distributed computer system cannot support more than two of the following three properties: consistency, availability, and partition tolerance.

See Initial considerations for multi-master topology for map sets that are not replicated.

A replication data grid infrastructure is a connected graph of catalog service domains with bidirectional links among them. Use a link between two catalog service domains to track data changes. For more information about how to set up communication between catalog service domains for multi-master replication, see Available topologies for multi-master replication.

Also, depending on the requirements of the environment, you can optimize the topology design for multi-master replication by taking several factors into consideration: arbitration, linking, and performance. Read more at Topology considerations for multi-master replication.

Parent topic:

Cache topology: In-memory and distributed caching

Related concepts

Local in-memory cache

Peer-replicated local cache

Distributed cache

Embedded cache