The GridGain Systems In-Memory Computing Blog
In this post, I will cover the changes in Apache® Ignite™ 2.0/2.1 (which tracks to GridGain 8.0/8.1) that are important when implementing a project in Ignite. Then we will discuss the easiest way to setup a cache and just use the basic functionality of the Data Grid.
So, Apache Ignite 2.0 & 2.1 have dropped! This is awesome news for you as a user. This is fun times for us at GridGain…
In-memory databases, data grids and computing platforms just cannot put aside the existence -- and necessity -- of good old-fashioned disk drives. The performance boost given by RAM is tempting and promising but almost nobody wants to lose data. Services and applications call for durability unless the data is of no value to them or floods into the system at such a rate that you can…
My colleague Akmal B. Chaudhri presented a webinar earlier this week where he looked in detail at Apache® Ignite™ architecture's ACID-compliant transactional subsystem.
After watching his webinar, recorded below, you'll have a better understanding of why companies in many industries, including large banks and financial institutions, trust Apache Ignite and make it their platform of…
The Apache Ignite Service Grid will be the subject of this article in this blog series.
Service Grid
The main feature of the Apache Ignite Service Grid is to deploy services onto a cluster with availability and fault-tolerance. A counter or an ID generator would be simple examples of services.
A major use-case for the Service Grid is to deploy a Singleton. There are a number of different types…
This is the fifth article in this blog series and I will focus this time on the support for a distributed SQL database in Apache® Ignite™.
Distributed SQL database
Today, SQL is still a very popular language for data definition, data manipulation and querying in database management systems. Although often associated with Relational database systems, it is now used far more widely with many non-…
This is the fourth article in this blog series and I will focus this time on the Streaming component of Apache Ignite.
Streaming Grid
Streaming represents data that continuously enters a system. The quantity of data may vary in size. The challenge is to store the streamed data and process it without running out of memory. To achieve this processing, the concept of a sliding window is used. This…
Figure 1 shows a high-level component view of Apache Ignite. So far in this blog series, I have briefly discussed Clustering and Deployment and the Data Grid.
Figure 1. Main components of Apache Ignite
I mentioned in the previous article that I could cover the SQL Grid next. However, because of late-breaking developments, I have postponed this for a few weeks. Instead, I will focus on the…
If you’re in IT and working for a bank or financial institution with a growing e-banking audience, then Lieven Merckx has a story that you’ll be very interested in.
A 32-year veteran IT architect, Lieven works with the team that’s been strengthening electronic retail banking offerings at ING Bank Belgium with in-memory computing technologies to meet rapidly growing customer demand for mobile…
In the previous article, I discussed my motivation for writing this blog series. Also presented was the high-level component view of Apache® Ignite™, shown in Figure 1.
Figure 1. Main components of Apache Ignite
The previous article also briefly introduced Clustering and Deployment. This article will focus on the Data Grid.
Data Grid
In Apache Ignite, a Data Grid can be thought of as a…
Peter Zaitsev, CEO and co-founder of Percona, says there are several key strategic benefits of using the Apache® Ignite™ in-memory computing platform instead of Memcached, Redis, Elastic or even Apache Spark.
I had the opportunity this week to connect with Peter and ask him about this and more questions as he prepares for next month's In-Memory Computing (IMC) Summit in Amsterdam…