The GridGain Systems In-Memory Computing Blog

RSVP now for our Dec. 12 webinar and learn how to complement a Relational DBMS for Hybrid Transactional/Analytical Processing (HTAP) by leveraging the massive parallel processing and SQL capabilities of Apache Ignite. Details here. You'll also learn how to use Apache Ignite as an In-Memory Data Grid that stores data in memory and boosts applications performance by offloading reads from a…
This post takes a closer look at Apache Ignite’s C++ API (called Ignite C++). It's intended primarily for C/C++ programmers. Ignite and Ignite С++ Ignite C++ is built on top of Ignite Ignite С++ starts the JVM in the same process and communicates with it via JNI .NET, C++ and Java nodes can join the same cluster, use the same caches, and interoperate using common binary protocol Java…
Last week my colleague Valentin Kulichenko, lead architect at GridGain Systems recorded a webinar explaining how companies have been using Apache® Ignite™ to overcome today’s data challenges.  He demonstrated how companies have been using Ignite to add in-memory speed and unlimited horizontal scale to SQL with no rip-and-replace of the underlying database. The webinar, recorded Nov. 28, was…
Two Apache® Ignite™ experts will be delivering a couple of webinars tomorrow (Nov. 28)  – one explaining the nuances of Machine Learning with Ignite ML, and another documenting how to add speed and scale to SQL.   The great thing about GridGain webinars is that although they are live, interactive events, they are also recorded. So if you miss either of these, just register as normal even after…
One of the features of Apache® Ignite™ is its ability to integrate with streaming technologies, such as Spark Streaming, Flink, Kafka, and so on. These streaming capabilities can be used to ingest finite quantities of data or continuous streams of data, with the added bonus of fault tolerance and scale that Ignite provides. Data can be streamed into Ignite at very high rates that may reach many…
Regardless of how mature a data storage technology is, backing-up data is a laborious and difficult task that can cost time, increase stress levels -- and even hit your bottom line. If this sounds familiar, my colleague --  GridGain senior software engineer Ivan Rakov -- hosted a webinar recently that details how to make discreet backups in a distributed environment.  His Nov. 21 webinar was…
Digital transformations are arguably the most important initiatives for companies. They can literally make or break a business. This transformation is not easy because there’s a big digital divide between the speed, scale and computing needed for new digital channels and APIs, and what existing systems can deliver. Wouldn't it be great if there was a roadmap that got you from start to finish?…
Making stream processing scale requires making all the components (including messaging, processing and storage) scale together. Easier said than done. Until now.  My colleague Rob Meyer, who is head of outbound product management, explained how in his Oct. 10 webinar, available for free playback here.  Rob, alongside GridGain professional services consultant Alexey Kukushkin, shared some of the…
At a recent gathering of the Moscow Apache® Ignite™ Meetup, I talked about open-source communities, how to become a contributor and a committer and some reasons why you should participate.  Specifically, I was talking about the story of the Apache Ignite community. The limited time of the talk did not allow me to give more examples, so that was the inspiration for this post -- which is by the…
Challenged with scaling stream processing for your organization? Then you'll want to register for our webinar, "Best Practices for Stream Processing with GridGain® and Apache® Ignite™ and Kafka." This free, live webinar is scheduled for Oct. 10 at 11 a.m. PDT (2 p.m. EDT). Register here. Making stream processing scale requires making all the components -- messaging, processing, storage -- scale…