Database Caching (2024)

With Hazelcast Platform, nodes automatically discover and join the cluster as you grow it to meet increasing demands for low-latency performance, greater data volumes, and stricter SLAs. Hazelcast clusters have no single-point-of-failure. Their peer-to-peer network forms the basis for a robust scale-out caching solution.

Hazelcast ensures high availability by leveraging data replication, in which data is copied across the grid (each copy is known as a “backup” in Hazelcast terminology) so that failure of any node does not bring down the grid or its applications, nor does it result in data loss. Hazelcast Platform automatically and dynamically handles the partitioning of data to ensure continuous availability and transactional integrity in the case of node failure.

In addition to elasticity and resiliency, Hazelcast provides utility classes that developers can use for distributed processing across data stored in memory in the cluster. These include continuous query interfaces for complex event processing applications, topics for high-speed messaging applications, a predicate Java API for SQL-like queries against NoSQL key-value data, and listeners and entry processors for high-speed data operations.

Hazelcast Platform ships out of the box with multiple caching implementations that plug-and-play with best-of-breed open industry standards including Memcached, Hibernate, Spring, and JCache. Developers can port applications written in these standards to a Hazelcast cluster without modifications. This enables organizations to quickly plug in Hazelcast Platform and benefit from elasticity and resiliency while leveraging APIs that enable powerful new ways to access distributed data.

Database Caching (2024)
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