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In-Memory Data Fabric

Friday, August 4, 2017 | Akmal B. Chaudhri
In this article I will focus on the new Machine Learning (ML) Grid. This is in development, but already offers a number of capabilities that may be very useful to Data Scientists. Machine Learning (ML) Grid Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers are able to find hidden…
Wednesday, July 12, 2017 | Akmal B. Chaudhri
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…
Thursday, July 6, 2017 | Akmal B. Chaudhri
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-…
Friday, June 30, 2017 | Akmal B. Chaudhri
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…
Thursday, June 15, 2017 | Akmal B. Chaudhri
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…
Thursday, June 1, 2017 | Akmal B. Chaudhri
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…
Thursday, May 25, 2017 | Akmal B. Chaudhri
I recently joined GridGain as a Technology Evangelist. My role is to help build the global Apache® Ignite™ community and raise awareness through presentations and technical writing. My background is database systems and I have no previous experience with Apache Ignite. So, in this series of articles, I will share what I learned about Apache Ignite as a beginner and I hope that this will also be…
GridGain Enterprise Edition 7.8 adds Support of In-Memory SQL Grid and Advanced GridGain Web Console Features
Thursday, March 23, 2017 | Denis Magda
Introducing GridGain Enterprise Edition 7.8, available for download now (includes a free 30-day trial), featuring enterprise-level tools like the GridGain Web Console Management and Monitoring tool built atop of the Apache® Ignite™ Web Console. Features include high availability and fault tolerance with a GridGain Web Console deployment, queries monitoring and cancellation, usage tracing and more…