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Thomas Krafft

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Top Stories by Thomas Krafft

As increasing numbers of industry leading companies look to new technologies to speed their real-time services and Big Data applications, GridGain Systems, leading developer of scalable, distributed in-memory compute and data grid technologies for real-time data processing, is strongly positioned to serve the demand. This week, GridGain announced the release of an entirely new suite of solution-focused products built around the company’s leading in-memory and world’s fastest MapReduce technologies, expanded enterprise consulting and other professional services, advanced DevOps management and monitoring capabilities now available with all products, and out-of-box integration with virtually any existing data source, Hadoop-based systems, and Java, C++, .NET, Android and iOS applications. Specifically related to GridGain’s new products, the company now offers three w... (more)

GridGain and Grid Dynamics Enable eCommerce and Big Data Solutions

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 ... (more)

Counting Words In Real Time On GridGain

We have promised a while back to publish the code from live coding GridGain presentation we did at QCon London earlier this year. Since presentation was in Scala, the code we will be posting here is in Scala. First a brief intro. We all know Hadoop’s counting words example which takes a file with words and then produces another file with number of occurrences next to each word. Hadoop does this example very well, however the main caveat with Hadoop’s example is that it is not real time. The counting words example we did at QCon actually counted words in real time. The program wa... (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)

You’re invited: 7/26 – Live Coding In-Memory Big Data with GridGain

GridGain will be hosting a webinar Thursday, July 26, 2012 at 3pm EST / 12pm PST during which GridGain’s CTO, Dmitriy Setrakyan, will be live coding GridGain examples in Java. Dmitriy will cover the following examples: How to distribute simple units of work to the grid. Collocation of computation and data. A full Streaming MapReduce example that performs SQL queries on streaming in-memory data. This is a fantastic opportunity to see how easy it is to get started with GridGain, so register now and join us for “Live Coding In-memory Bid Data with GridGain.” ... (more)