GridGain In-Memory Data Fabric

GridGain In-Memory Data Fabric is a scaled technology of applications with a high volume of data processing and acceleration of transactions.

2017: There was a release of GridGain 8.1

On June 21, 2017 GridGain Systems submitted the version of the in-memory computing GridGain 8.1 platform.

GridGain 8.1 expands SQL possibilities of the GridGain platform with the SQL Data Definition Language (DDL) functions in addition to the existing support of DML and ACID transactions. The release provides optimal performance in hybrid infrastructures "memory + a disk" due to the Persistent Store function. For the organizations working with Persistent Store, the GridGain Ultimate Edition platform offers function of backup of pictures of a cluster which is recommended when using of the architecture focused on memory in crucial environments.

Data Definition Language

In the previous version of GridGain there was a support of languages DDL in the built-in storage SQL Grid allowing to set and change indexes during operation without reset of a cluster. Now users can manage caching and schemes of SQL bases through the CREATE and DROP commands. It allows to be connected to GridGain via the JDBC or ODBC drivers and to completely configure a cluster using DDL commands. As a result the user does not need to use Spring XML, Java or .NET options for a cluster configuration. Instead, it can work with the GridGain platform with support of ANSI SQL-99, using standard commands DDL and DML.

Persistent Store

Persistent Store is the distributed disk storage with support of ACID and ANSI SQL - 99 is integrated into Apache Ignite which is transparent with GridGain as an optional disk layer (it can be unrolled on SDD, SSD, Flash, 3D XPoint and other technologies of memory). Persistent Store saves all data on a disk, placing only set by the user, data necessary at a given time in memory. Connecting Persistent Store, users do not need to keep all active data in memory or to warm up RAM with the subsequent restart of a cluster to use system capability in-memory. Persistent Store stores all set of data and the SQL indexes on a disk, doing GridGain completely functional on disks. The combination of a new feature and expanded SQL opportunities of the platform allows GridGain to serve as the distributed transaction SQL database with use of both disks, and memory for support of the existing scenarios. Persistent Store helps the organizations to maximize return from investments, setting balance between costs for infrastructure and performance of applications due to regulation of amount of data which are stored in memory.

Pictures of clusters

In the GridGain Ultimate Edition platform the Cluster Snapshots function appeared. Pictures of clusters are important for production implementations of GridGain using Persistent Store. They allow to create both complete, and incremental pictures which can be used as recovery point or as a source of comparative data in intermediate and test environments. It is possible to configure pictures under the user's business challenges using the GridGain Web Console and Snapshot Command Line Tool tools.

Exchange of classes with logic between .NET cluster nodes

In several versions of GridGain the peer-class loading function supported Java. It eliminated need to manually implement the Java or Scala code on each node of a cluster and to reinstall it at each change. Necessary classes are loaded or removed as necessary. With GridGain 8.1, .NET developers have the same opportunity. Assembly of .NET can be automatically a predzagruzhena on already working .NET cluster cell now if local implementation of a problem of distributed computing is absent. Removal is also performed automatically.

C ++ for development

Developers can plan and create tasks of GridGain Compute Grid using C ++ and send them to work in GridGain cluster. Ignite.C ++ will automatically serialize, will deserialise and executes calculations.

GridGain 8.1 is a mature in-memory computing platform of new generation which can profitable be used as a grid of data in memory with the existing RDBMS, NoSQL or Apache Hadoop bases. It can also work as the independent distributed SQL database, using a new feature of Persistent Store. Expanded support of SQL DDL simplifies work with GridGain using standard SQL commands, and the Persistent Store and Cluster Snapshots functions allow to work with the platform in broader spectrum of production applications. Each organization can set balance between operating costs and performance of applications, regulating the amount of data which are stored in memory. With enhanced capabilities of .NET and C ++ development teams can use already available skills for work with GridGain. In general, the platform of new generation GridGain 8.1 gives to the organizations the chance to place the computing platform focused on memory as a strategic core of the infrastructure of storage and data processing. Abe Klyaynfield, president and CEO of GridGain

2016: GridGain In-Memory Data Fabric

On September 15, 2016 the GridGain System company provided the product GridGain In-Memory Data Fabric on a cloud platform of Microsoft Azure.

A system will help banks and the companies to use in the field of financial services advantages of the integrated cloud services Microsoft to deploy the distributed, mass and parallel solution of GridGain for transfer of calculations in RAM of the computer.

Representation of GridGain In-Memory Data Fabric, (2016)

The software of GridGain In-Memory Data Fabric on the basis of Apache Ignite provides scaling of applications with a high volume of data processing and acceleration of transactions in 1 thousand times without replacement of the existing databases, in comparison with processing on a disk.

Software executes high-speed ACID transactions, streaming in real time and effective analytics within uniform complex data access. The solution supports work, the applications as existing, and upgraded in the distributed, mass and parallel architecture on the available hardware which is easy for scaling adding of additional nodes in the computing system. The GridGain In-Memory Data Fabric platform does not require, or requires the minimum changes in the application or levels of the database for architecture on the basis of RDBMS, NoSQL or Apache Hadoop.

The release of GridGain In-Memory Data Fabric on Microsoft Azure is an important step for the best service of requirements of our fast-growing base of clients. In particular, we see that solutions of GridGain are actively used by top banks and financial services providers who at the same time transfer the infrastructures to "cloud". These users will be able to work now with the reliable and productive platform on which it is easy to deploy solutions of GridGain for online processing of transactions, a business intelligence online or both scenarios at the same time. Thanks to flexibility of the Azure platform, our clients will have a choice between outsourcing of all server architecture or transfer of peak loading in "cloud" on demand. Abe Klyaynfield, president and CEO of GridGain

Considering that the largest banks worldwide gradually pass to Microsoft Azure, to make the solutions available on this platform is a natural step for GridGain. Thereby the company satisfies needs of the leading suppliers of financial services which need to deploy the solution in-memory computing in "cloud". Emergence of the solutions GridGain In-Memory Data Fabric in Microsoft Azure Marketplace shop helps our general clients with the financial services industry quickly and conveniently to begin to use GridGain. Nichole Hershkovits, the senior director on product marketing of Microsoft Azure