Previously, we looked at how to use GridGain® and Kafka® using a local installation. Let’s now look at an example where we deploy in the Cloud. We will use the GridGain Cloud and the Confluent Cloud environments.
If you'd like to follow along with this example, ensure that you meet the required prerequisites first:
Create an account on the GridGain Cloud
Create an account on the Confluent…
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…
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…
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…
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…
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…
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…
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…
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…