Featured Post

Introducing the GridGain Forums!

I'm proud to announce the launch of the GridGain Forums! In addition to fostering peer-to-peer discussions, the Forums are designed to connect our experts with users of GridGain software.
read more

Previous Entries

Introduction Apache® Ignite™ provides support for a number of major programming languages. Recently, support for additional programming languages has also been added using what is termed as a Thin Client. New Thin Clients include Python, PHP and Node.js. The characteristics of a Thin Client are as follows: It is a lightweight Ignite client that connects to a cluster using a standard socket…
read more
GridGain Basic Support was unveiled today -- the first support offering designed exclusively for Apache® Ignite™ users.  GridGain Support for Apache Ignite enables organizations with new or existing Apache Ignite deployments to access the deep expertise of GridGain’s support engineers to troubleshoot performance or reliability issues and identify configuration optimizations, workarounds or…
read more
Recently a new version of Apache® Ignite™ was released. Let’s examine some of the new features from the .NET perspective.   Thin .NET Client   Before Apache Ignite version 2.4 (in both Java and .NET), there were two cluster connection modes: Server and Client. Basically, the difference between the client mode and server mode boils down to the following: the client nodes don’t store data and…
read more
In summing up the business side of GridGain for last year (compared with the community side that I usually blog about), the company continued strong momentum throughout 2018. Let's take a closer look.   Key achievements during the year included 200 percent year-over-year growth in new customers, numerous industry honors, key product and service innovations and increasing popularity of the In-…
read more
Introduction In the previous article, we discussed the steps required to sign-up for a GridGain® Cloud account, created our first cluster, described the two built-in SQL demos and briefly reviewed the monitoring capabilities. In this article, let's look at examples of how to connect to a GridGain Cloud Cluster using two different programming languages. Recall that in the previous article, we…
read more
In a previous post, we shared an Apache® Ignite™ primer for people new to this exciting this open source project. In it, we touched upon Ignite's key features. Today I'll focus on the commonly asked question: Does Ignite have persistent storage or memory-only storage? The answer? Both. Native persistence in Ignite can be turned on and off. This allows Ignite to store data sets bigger than can…
read more
Introduction In 2018, GridGain® previewed GridGain Cloud. GridGain Cloud enables a GridGain cluster to be run as a service. It supports both distributed in-memory computing and persistence. A number of APIs are supported: JDBC ODBC Binary Protocol and Thin Clients REST We will look at examples of some of these APIs in this article series. GridGain Cloud provides compatibility with GridGain…
read more
GridGain's Rob Meyer continues his series on in-memory computing best practices this Thursday when he'll be talking about digital transformation and why delivering a responsive digital business is not possible at scale without in-memory computing. The webinar is titled, "In-Memory Computing Best Practices: Developing New Apps, Channels and APIs" and I suggest registering now to reserve your spot…
read more
We’ve got a busy week ahead for in-memory computing enthusiasts. A meetup tonight in New York City and two in-memory workshops tomorrow evening in Boston and Silicon Valley.    GridGain and Apache® Ignite™ evangelist  Akmal Chaudhri is in New York City for tonight’s  NYC In-Memory Computing Meetup. His talk is titled, "Relational DBMSs: Faster Transactions and Analytics with In-Memory Computing…
read more
Introduction Apache® Ignite™ has supported Machine Learning capabilities for a while now. With the release of Ignite v2.7, additional Machine Learning and Deep Learning capabilities have been added, including the much-anticipated support for TensorFlow™. TensorFlow is an open-source library that can be used for numerical computations and for performing Machine Learning at scale. It is also very…
read more