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Hazelcast adoption grows as open source IMDG embedded in multiple Apache projects

First Published 17th July 2017

Chris Law, Future Grid

Chris Law, Future Grid

Palo Alto, California - Hazelcast, the open source in-memory data grid (IMDG), has released figures demonstrating an increase in phone homes and downloads - in 2017 these have increased by 54% reaching 26 million per month. Apache Gora is the latest Apache project to use Hazelcast IMDG.

Gora is an open source framework which provides an in-memory data model and persistence for big data. Alongside Gora, Hazelcast IMDG has also been deployed in four other Apache projects: Apache Camel, Apache TomEE, Apache Shiro and Apache Karaf.

A commercial project by Future Grid in Australia integrated Hazelcast IMDG with Apache Cassandra. Future Grid amalgamated the two open source solutions to support high velocity IoT use cases for a number of Energy clients. A fundamental limitation of Cassandra is that it is disk-based, not an in-memory database. This means that read performance is always capped by I/O specifications, ultimately restricting application performance at scale. Integrating Hazelcast IMDG with Cassandra can make more data available and effective. The combined solution is intended to maintain the availability and horizontal scalability of Cassandra, while delivering performance using the Future Grid Platform that is 1000x faster than disk-based approaches due to Hazelcast IMDG.

Chris Law, Co-Founder and CEO at Future Grid, said: "We implemented Hazelcast IMDG at the core of our products in-memory capability, while also integrating it with a range of purpose built technologies to deliver the platform our customers required. For example, Hazelcast IMDG is integrated with Cassandra which provides internal data storage for low speed reference data while maintaining a distributed grid architecture. We found integrating Hazelcast with Cassandra was a very straightforward process."

Hazelcast has also become a member of Eclipse MicroProfile. The MicroProfile is a baseline platform definition that optimizes Enterprise Java for a microservices architecture and delivers application portability across multiple MicroProfile runtimes. The initially planned baseline is JAX-RS + CDI + JSON-P, with the intent of community having an active role in the MicroProfile definition and roadmap. Community members will continue to innovate independently, but the MicroProfile allows collaboration where there is a commonality. By leveraging commonality to define a baseline platform, developers will have a degree of application portability with multiple implementations to choose from.

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