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Scalability overview

WebSphere eXtreme Scale is scalable through the use of partitioned data, and can scale to thousands of containers if required because each container is independent from other containers.

WebSphere eXtreme Scale divides data sets into distinct partitions that can be moved between processes or even between physical servers at run time. You can, for example, start with a deployment of four servers and then expand to a deployment with 10 servers as the demands on the cache grow. Just as you can add more physical servers and processing units for vertical scalability, you can extend the elastic scaling capability horizontally with partitioning. Horizontal scaling is a major advantage to using WebSphere eXtreme Scale over an in-memory database. In-memory databases can only scale vertically.

With WebSphere eXtreme Scale, you can also use a set of APIs to gain transactional access this partitioned and distributed data. The choices you make for interacting with the cache are as significant as the functions to manage the cache for availability from a performance perspective.

Scalability is not available when containers communicate with one another. The availability management, or core grouping, protocol is an O(N2) heartbeat and view maintenance algorithm, but is mitigated by keeping the number of core group members under 20. Only peer to peer replication between shards exists.

Distributed clients

The WebSphere eXtreme Scale client protocol supports very large numbers of clients. The partitioning strategy offers assistance by assuming that all clients are not always interested in all partitions because connections can be spread across multiple containers. Clients are connected directly to the partitions so latency is limited to one transferred connection.

  1. Data grids, partitions, and shards
  2. Partitioning
  3. Placement and partitions
  4. Single-partition and cross-data-grid transactions
  5. Scaling in units or pods

Related concepts

Product Overview
WebSphere eXtreme Scale overview
Cache overview
Cache integration overview
Availability overview
Transaction processing overview
Security overview
REST data services overview
Spring framework
Tutorials, examples, and samples

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