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Database Caching

Hazelcast is the leading open source in-memory data grid solution. It enables organizations to predictably scale mission-critical enterprise applications by providing in-memory access to frequently used data. To meet service-level agreements (SLA) as customer data expands exponentially, organizations of all sizes are turning to in-memory solutions to scale applications, offload over-burdened shared data services and provide availability guarantees.

Database Caching Architecture Diagram

First and foremost, Hazelcast database caching stores frequently accessed data in-memory and across an elastically scalable data grid. This enables any network of machines to dynamically cluster and pool both memory and processors to accelerate application performance. Nodes automatically discover and join the cluster which grows to meet increasing demands for low-latency performance, data volume and SLAs.

Hazelcast clusters have no single-point-of-failure and form a peer-to-peer network that forms the basis for a robust scale-out caching solution. Data is backed up across the grid so that failure of any node does not bring down the grid or its applications. This provides a dynamic form of high availability based on the same mechanism of dynamic discovery used for growing the cluster. Hazelcast automatically and dynamically handles the partitioning of data which ensured continuous data availability and transactional integrity even in the case of node failure.

In addition to elasticity and resiliency, Hazelcast provides utility classes that developers can use to provide distributed processing across in-memory data within the cluster. These include Continuous Query interfaces for Complex Event Processing applications, Topics for high speed messaging applications, Predicate API for SQL like queries against NoSQL Key Value data and Listeners and EntryProcessors for high-speed data operations.

Hazelcast also ships out of the box with multiple caching implementations that plug-and-play with best-of-breed open industry standards. These include:

  • Memcached
  • Hibernate
  • Spring
  • JCache

Applications written to these standards can be deployed on top of a Hazelcast cluster without being changed. This allows organizations to quickly plug in Hazelcast and benefit from elasticity and resiliency while enabling new APIs that enable powerful new ways to access distributed data.