In-Memory Data Grid
What is an in-memory data grid?
An in-memory data grid is data management software that enables:
- Scale-out Computing: every node adds their CPU to the cluster
- Resilience: nodes can fail randomly without data loss or significant performance impact to running applications
- Programming Model: a way for developers to easily program the cluster of machines as if it were a single machine
- Fast, Big Data: it enables very large data sets to be manipulated in main memory
- Dynamic Scalability: nodes (computers) can dynamically join the other computers in a grid (cluster)
- Elastic Main Memory: every node adds their RAM to the cluster’s memory pool
In-memory data grids are often used with databases in order to improve performance of applications, to distribute data across servers, clusters and geographies and to manage very large data sets or very high data ingest rates.
Why Hazelcast IMDG?
For those familiar with in-memory data grid solutions such as:
- Oracle Coherence
- Software AG Terracotta
- Pivotal Gemfire
and others, Hazelcast will quickly and easily be understood as an open source alternative to this class of solutions. Open source software provides a number of proven advantages as a software licensing model.
As the leading open source in-memory data grid, Hazelcast IMDG provides rich features such as Entry Processing and distributed Execution Services that go beyond caching data and enable programmers to access the distributed processing power of the grid.
Instead of reading about it on a web site, the best way to experience the differences between solutions are to try them out. We encourage everyone to try Hazelcast IMDG.