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Thomas Krafft

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Grid Dynamics, an eCommerce technology solutions company, and GridGain Systems, makers of an open source in-memory platform for Big Data processing, on Wednesday announced the expansion of their partnership which began in 2008. Grid Dynamics provides personalization and big data solutions for large-scale eCommerce companies, GridGain’s Java based open source middleware platform allows organizations to perform real time processing and analytics on live big data. “GridGain has always been an important component within the portfolio of technologies we use to build next-generation software products and platforms for our enterprise customers,” says Victoria Livschitz, CEO of Grid Dynamics. “GridGain’s mature in-memory compute and data grid platform can deliver analytics capabilities necessary to improve revenues and conversion rates for eCommerce companies far more eff... (more)

GridGain 4.2 Released!

We are happy to announce that GridGain 4.2 is released! This release includes several new exciting feature as well as the host of performance optimizations that we’ve included. This release is 100% backward compatible with 4.x product line and we recommend anyone on 4.x version to update as soon as possible. Now – let’s talk about new features… Delayed Preloading In GridGain 4.2 we’ve introduced support for delayed preloading. Dmitriy Setrakyan wrote an excellent blog detailing this new functionality. Essentially, whenever a new node joins the grid or an existing node leaves th... (more)

Micro Cloud in Your JVM: Code Example

Few days ago I blogged about how GridGain easily supports starting many GridGain nodes in the single JVM – which is a huge productivity boost during the development. I’ve got a lot of requests to show the code – so here it is (next page). This is an example that we are shipping with upcoming 4.3 release (entire source code): import org.gridgain.grid.*; import org.gridgain.grid.spi.discovery.tcp.*; import org.gridgain.grid.spi.discovery.tcp.ipfinder.*; import org.gridgain.grid.spi.discovery.tcp.ipfinder.vm.*; import org.gridgain.grid.typedef.*; import javax.swing.*; import java... (more)

Practical Introduction to Streaming MapReduce

In this article I’ll introduce the concept of Streaming MapReduce processing using GridGain and Scala. The choice of Scala is simply due to the fact that it provides for very concise notation and GridGain provides very effective DSL for Scala. Rest assured you can equally follow this post in Java or Groovy just as well. The concept of streaming processing (and Streaming MapReduce in particular) can be basically defined as continues distributed processing of continuously incoming data streams. The obvious difference between other forms of distributed processing is that input dat... (more)

In-Memory Compute Grid… Explained.

Dmitriy Setrakyan provided an excellent explanation for In-Memory Data Grid (IMDG) in his blog http://gridgain.blogspot.com/2012/11/in-memory-data-grids-explained.html. I will try to provide a similar description for In-Memory Compute Grid (IMCG). PDF version of this article is available. IMCG – In-Memory Compute Grid One of the main ideas Dmitriy put forward is the importance of integration between in-memory storage (IMDG) and in-memory processing (IMCG) to be able to build truly scalable applications. Yet – the IMCG and its implementations are seen less frequently than IMDG ma... (more)