The GridGain Systems In-Memory Computing Blog

Note: This is post 1 in the blog series: Continuous Machine Learning at Scale with Apache Ignite. For post 2 click here and for post 3 click here. This is my first blog post in a series that discusses continuous machine learning at scale with the Apache® Ignite™ machine learning (ML) library. In this article, I’ll introduce the notion of continuous machine learning at scale. Then, I’ll discuss…
Kafka with Debezium and GridGain connectors allows synchronizing data between third party Databases and a GridGain cluster. This change data capture based synchronization can be done without any coding; all it requires is to prepare configuration files for each of the points. Developers and architects who can’t yet fully move from a legacy system can deploy this solution to give a performance…
Memory access is so much faster than disk I/O that many of us expect to gain striking performance advantages by merely deploying a distributed in-memory cluster and start reading data from it. However, sometimes we overlook the fact that a network interconnects cluster nodes with our applications, and it can quickly diminish the positive effects of having an in-memory cluster if a lot of data…
My acquaintanceship with PostgreSQL started back in 2009 - the time when many companies were trying to board the social networking train by following Facebook's footsteps. An employer I used to work for was not an exception. Our team was building a social networking platform for a specific audience and faced various architectural challenges. For instance, soon after launching the product and…
Ease-of-use is one of the core requirements at GridGain® which influences the way we see and build our products. While in-memory computing is a complex topic, the application development experience should not be equally complex. In the coming months you will see changes to GridGain and Apache® Ignite™ that will simplify Core APIs and the way that you debug running applications. In keeping with…
GridGain recently started publishing the Best Practices for Digital Transformation with In-Memory Computing (IMC) eBook series. The series captures some of the best practices for putting the right people, processes, and technology in place that helped early adopters succeed with their digital transformations. This blog post summarizes the first eBook in the series and outlines the best…
In a bid to speed the development and rollout of applications built on GridGain or Apache Ignite, GridGain Systems has just launched "GridGain Developer Bundles." These bundles include Support, Consulting and Training for GridGain Community or Enterprise Edition. The new Developer Bundles help companies implementing Apache® Ignite™ or GridGain speed the development and rollout of real-time,…
It’s hard to imagine that it’s been over 20 years since MySQL was created. There has been a lot of innovation and acquisitions since then, as well as consolidation of many MySQL options: Alzato Tech, the original NDB Cluster technology, was aquired by MySQL AB in 2003 InnoDB, the main storage engine for MySQL, was acquired by Oracle in 2005 Percona released Percona Server for MySQL in 2006…
The GridGain Data Lake Accelerator, released today, is an in-memory solution for digital businesses that need to enrich operational data with historical data stored in data lakes to improve real-time analytics and decision automation. A data lake is a system or repository of data stored in its natural format, usually object blobs or files. A data lake is usually a single store of all enterprise…
With some 30 breakout sessions, the In-Memory Computing Summit Europe 2019, happening June 3-4 in London, is a must-attend learning event for data scientists across the region. For today’s blog post I had the chance to speak with one of the many in-memory computing experts who will be speaking there: Chris Jenkins, senior director of In-Memory Technology at Oracle. His talk is titled, “Cloud…