Information and Insights on In-Memory Computing
Tuesday, October 25, 2016
The GridGain Enterprise Edition, based on Apache® Ignite™, is now available on the Amazon Web Services (AWS) Marketplace. The GridGain in-memory computing platform allows organizations across multiple industries to rapidly and effectively deploy GridGain’s distributed, massively parallel, in-memory computing solution on AWS.
Tuesday, October 18, 2016
Fraud has evolved from a disorganized criminal activity into a sophisticated multi-billion dollar business. Fraud committed within financial services is causing loss of revenue, institution’s reputation, shareholder’s confidence and customer loyalty. As the fraudulent schemes become more sophisticated, so should the ways of fighting them.
Monday, October 17, 2016
Introduction Nowadays many companies are basing their applications and solutions on
Thursday, October 6, 2016
In-memory computing allows users to process terabytes of data in real-time and across many different applications and underlying databases. In-memory computing is gaining momentum in industries such as financial services, fintech, software/SaaS, telecommunications, ecommerce, online services, and retailers for its ability to transact and analyze large amounts of data in real-time. As the in-memory computing industry grew rapidly over the past few years, it became increasingly confusing to navigate between different types of solutions offered by in-memory computing vendors.
Wednesday, September 28, 2016
Recently Hazelcast rolled out its new version - Hazelcast 3.7. This new version incorporates a lot of performance related improvements that, according to Hazelcast, provide a 30% performance boost compared to its previous versions. We, at GridGain, consistently spend a significant amount of resources to make sure that the performance of our products show the best results, and hence, are curious to see how close Hazelcast could get to GridGain in terms of performance.
Wednesday, September 21, 2016
The GridGain Enterprise Edition, based on Apache® Ignite™, is now available on the Microsoft Azure Marketplace. The GridGain in-memory computing platform dramatically accelerates and scales out existing data-intensive applications without ripping and replacing existing databases. GridGain enables unlimited scalability and tremendous speed. Query times are up to 1,000,000x faster than disk-based systems.
Friday, September 16, 2016
I have been attending (and speaking) at the annual Apache® Cassandra™ Summit for 4 years, but this was my first time as a sponsor on the Expo floor. My time in the Cassandra ecosystem has proven to be a powerful lesson in how fast open source communities can grow and evolve. In 2013, there were less than 1,000 attendees. By 2015, over 3,500 were at last year’s Summit. This year, the event was at the massive San Jose Convention Center, rarefied air for a database that is younger than my home computer (!), and shows the momentum in this community.
Tuesday, September 6, 2016
”Apache Spark™ and Apache Ignite™ for Fast Data” Webinar on September 7, 2016 Apache Spark and Apache Ignite are two of the most popular open source projects in the area of high-performance Big Data and Fast Data. Both technologies are in-memory computing solutions to Big Data challenges but they target different use cases and, in many instances, are complementary.
Tuesday, August 9, 2016
About 2 months ago I joined GridGain Systems and was introduced to Apache Ignite. At my very first meetup last month in New York, someone challenged me on the subject of how Ignite could guarantee ACID level consistency if Ignite was a highly available distributed system. I was familiar with CAP Theorem from my work with Apache Cassandra, but for the first time in my otherwise data warehouse heavy career, I was having to stare ACID concepts right in the face.
Monday, August 1, 2016
In-Memory Computing enables processing up to 1,000,000x faster than with disk-based storage and scalability to hundreds of TBs by adding commodity nodes to the cluster. It is characterized by using high-performance, integrated and distributed memory systems to compute and transact on large-scale data sets in real-time. The GridGain In-Memory Data Fabric for .NET delivers outstanding performance for a wide set of in-memory computing use cases on top of the .NET platform. Use cases include high performance computing, CEP, and data streaming.
Tuesday, July 19, 2016
One of the biggest drivers of the explosion of data in the financial services sector, along with the need to process that data at ever-faster speeds, is the requirement to comply with the many government regulations that have been imposed since the global financial crisis of 2008-09.
Monday, June 20, 2016
This week I was excited to finally attend QCon NY after having read so many tweets from the event in the past years. I had expected the majority of attendees to be startups, so I was surprised to see many established companies at the event. The conference was divided into several tracks over the course of three days. Of these tracks, the microservices and containers tracks seemed to be the most popular. Many of these sessions were standing room only.
Tuesday, June 14, 2016
GridGain recently won two more awards to add to it’s growing list of accolades.
Friday, June 10, 2016
There is no doubt that Spark is one of the hottest (pun intended) technologies available to data engineers today. And the buzz on the exhibitor floor at the Hilton San Francisco for this year's Spark Summit did not disappoint. All the major players who supply software and hardware tools for next generation app development were present and accounted for, including some intriguing new players to the market.
Tuesday, May 31, 2016
The Internet of Things (IoT) is one of the most exciting and significant technology revolutions in the world today. Though there are countless IoT systems in operation at fledgling start ups and established corporations alike, most experts agree the industry is still in its infancy. It is estimated that by 2020 there will be over 30 billion devices wirelessly connected to the Internet.