In-memory computing can provide tremendous benefits for the 5G ecosystem. We’ve seen the marketing for the fifth-generation mobile networks. The benefits of 5G for end-users are easy to understand. Speeds faster than your home broadband and latencies only a little slower promise to be game-changers for consumers, enhancing existing applications and opening open entirely new categories that we…
The GridGain Systems In-Memory Computing Blog
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…
Introduction
The Spark SQL engine provides structured streaming data processing. The benefit here is that users can implement scalable and fault-tolerant data stream processing between the initial data source and final data sync.
You can read more about it here:
https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html
Apache Ignite provides the…
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…