GridGain 4.0 Now Available!

GridGain Systems’ Java based open source in-memory data and compute grid platform allows companies to perform real time (sub-second or better) processing and analytics on live big data. GridGain is open source and available in a free Community Edition (GPLv3), OEM and Enterprise Editions. You can download, setup and create a fully functioning, distributed MapReduce application that can work on 1 to 1,000+ nodes in about 5 minutes.

What's new in release 4?

Management & Monitoring Dashboard for Enterprise Dev/Ops

Enterprise and OEM Editions of GridGain now include GridGain Visor that provides both an easy-to-use GUI console, as well as a scriptable environment for managing and monitoring GridGain distributed topologies. The Visor GUI console allows Operations personnel to perform all major management and monitoring operations, such as:

  • Various Node Actions
  • Topology View with Metrics
  • Metrics For Any Projection
  • Comprehensive Historical Charts
  • Advanced Grid-Wide Events
  • Ability to specify the time span for chart views
  • Nice in-place filtering for events in Dashboard
  • Quick access to event details

More Language Clients: Native .NET support

With 4.0.1 we are introducing native support for .NET with our C# Client. Our C# Client provides native .NET/C# APIs for accessing both GridGain's In-Memory Data Grid and Compute Grid from outside of the GridGain topology context. Check out examples on GitHub. The C# Client is one of many native clients we're rapidly adding. Upcoming releases will include ObjectC iOS support, C++, PHP, Scala, Ruby, and more!

Improved Support for 32-bit and 64-bit Systems

GridGain now provides better out-of-the-box support for 32-bit and 64-bit systems, easing configuration and usage.

Affinity-Aware Native Clients

This basically means that when working with data grids, GridGain will automatically figure out on which node the data is stored and will route client requests to that node. Imagine the amount of network trips you can save by retrieving data directly from the node which is responsible for storing it (same goes for updates). This feature is available for all of our native clients, not only for Java, which makes GridGain into the only native cross -language distributed Real Time Big Data platform.

Memcached Binary Protocol Support

GridGain 4.0 Binary connectivity protocol supports a lot more than Memcached does. Essentially we have taken Memcached protocol as our starting point and significantly enhanced it with our own commands and features - while maintaining full compatibility. For example, you can configure security with proper authentication and secure sessions for remote clients, or you can execute MapReduce tasks, and get remote node topology.

Advanced Security and Authentication

In GridGain 4.0 we added the notion of secure grids. Grids can now request that nodes to be authenticated prior to joining them into the topology. The Authentication implementation is fully pluggable through our SPI-based architecture and comes with several implementations out of the box, such as Passcode or JAAS-based authentication. Additionally remote clients can also be required to authenticate themselves and once authenticated, they establish a secure session with the server. Both, authentication and secure-session SPIs are available in GridGain enterprise edition only.

Data Loaders + Hadoop HDFS Support

There are plenty of ways to load data into data grids, including using basic cache APIs or our support for bulk-loading of data from data stores. Data loaders make it easy to externally load data into grid by adding collocation with data nodes, sending concurrent data loading jobs and properly controlling the amount of memory consumed by data loading process.

1000+ Nodes Guaranteed Discovery

In this release we enhanced our TCP-based discovery protocol with enterprise-proven support for network segmentation and half-connected sockets. Our discovery protocol was tested on thousands of grid nodes on Amazon EC2 by us and by our customers to make sure there are no cluster or data inconsistencies. This protocol is already successfully running on several customer production deployments.

LevelDB Swap Space Implementation

In GridGain 4.0 you can load terabytes of data into cache. GridGain will try to fit as much of the data in memory as possible – the more grid nodes you have, the more memory is available for caching data. However, if you have more data than fits into the whole memory of the grid, you can use GridGain's LevelDB swap space implementation (which is based on Google LevelDB storage) to swap infrequently used data to disk. We have found that by using GridGain's LevelDB-based Swap Space in combination with SSD, we can efficiently store large amounts of data, with a fairly small disk footprint (using compression) and with very low latency performance. Additionally, our LevelDB implementation enhances our swap eviction policy to prevent infinite disk growth. GridGain's LevelDB Swap Space is available for both Java and Windows environments.

About GridGain Systems

GridGain Systems’ Java based open source middleware platform allows companies to harness live, big data for smarter, faster real time processing and analytics. Every 10 seconds, an installation of GridGain is started somewhere around the globe. Our customers include innovative web and mobile businesses, leading Fortune 500 companies, and top government agencies. GridGain is headquartered in Foster City, California. Learn more at http://www.gridgain.com and follow the company on Twitter @gridgain.