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
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
“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)
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…
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
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
import org.gridgain.grid.*; import org.gridgain.grid.spi.discovery.tcp.*;
import org.gridgain.grid.spi.discovery.tcp.ipfinder.*; import
org.gridgain.grid.typedef.*; import javax.swing.*; import
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)
Dmitriy Setrakyan provided an excellent explanation for In-Memory Data Grid
(IMDG) in his blog
I will try to provide a similar description for In-Memory Compute Grid
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)