The GridGain In-Memory Computing Performance Blog

Information and Insights on In-Memory Computing

Michael Griggs
Monday, November 28, 2016
On November 17th, one of our European GridGain Systems' consultants visited Madrid to present a paper at Big Data Spain entitled “Better Together: Fast Data with Apache Ignite & Apache Spark”.  The Big Data space has been growing rapidly over the past few years, with disk-based Hadoop systems and then hybrid disk and memory systems such as Apache Spark gaining significant mindshare.  Whilst Apache Spark focuses on the analytical/machine-learning end of the Big Data world, Apache Ignite is primarily used for high-performance transact
Prachi Garg
Wednesday, November 23, 2016
While most applications use distributed in-memory caching for fast data access, they heavily rely on relational databases for data persistence purposes. For such applications, Apache Ignite supports read-through and write-through modes to read/write the data from/to the underlying persistent store, respectively.
Tatiana Staffaroni
Tuesday, November 22, 2016
Join us on Wednesday, November 30, 2016 at 11:00 AM PDT/2:00 PM EDT for a webinar discussing tuning Apache® Ignite™ and GridGain for optimal performance with Valentin Kulichenko, Lead Architect at GridGain Systems.
Terry Erisman
Monday, November 21, 2016
When securities prices move, trading firms can make more money the faster they react. High-frequency securities trading is now the norm and financial services firms are incentivized to maximize the performance of their high-frequency trading infrastructure. Performance plays a critical role in each basic step of high-frequency securities trading, including obtaining market information, processing the information through prediction algorithms, and executing trades based on the information – all transaction-intensive.
Terry Erisman
Wednesday, November 16, 2016
I am pleased to announce the launch of the In-Memory Computing Planet ( website. IMCPlanet is a moderated community portal that encourages information sharing among in-memory computing community members. The website consolidates in-memory computing blogs and events from around the world, providing the in-memory computing community with a centralized location where they can find the latest information and events related to in-memory computing.
Terry Erisman
Tuesday, November 15, 2016
Banks and other financial services firms face a slow economic recovery, pessimistic economic forecasts worldwide, demands to improve their balance sheets, and more. As a result, banks are cutting costs, restructuring, optimizing business lines, and exiting less profitable activities – all while under pressure to satisfy new compliance regulations designed to protect against another economic meltdown.
Christos Erotocritou
Monday, November 14, 2016
After attending the European Spark Summit I felt the need to share a few words summarizing my experience and perception of it, which hopefully can provide insight to those who were not able to attend, or attended and want a vendor’s perspective of it. 
Tatiana Staffaroni
Thursday, November 10, 2016
In-memory computing solutions boost performance as a result of their key-value based architecture. However, both application and business needs require flexible SQL support. Many in-memory data grid (IMDG) solutions invent their own query engines or provide limited SQL support. Neither of these approaches meet real world needs. During this webinar, we will provide an overview of how typical IMDGs address this SQL support requirement.
Denis Magda
Wednesday, November 9, 2016
Almost any In-Memory Data Grid (IMDG) solution available can be used as-is without an underlying persistent storage layer. Based on my experience, there are different use cases and real production scenarios when the entire data set is fully located in an IMDG and it is not synced to disk at all. However, in a variety of deployments, companies still prefer to keep data both in memory and on disk. They do this to ensure that the data will not be completely lost if the whole IMDG cluster goes down or needs to be restarted.
Tatiana Staffaroni
Wednesday, October 26, 2016
Spread betting is an alternative to conventional trading that enables users to speculate on rising as well as falling market prices. Spread betting became one of the major global growth markets since the financial crisis of 2008. The reasons for this rise in popularity include preferential tax treatment, low entry and transaction costs, favorable conversion rates, wider bid offer spreads and less regulations.
Tatiana Staffaroni
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. 
Tatiana Staffaroni
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. 
Denis Magda
Monday, October 17, 2016
Introduction Nowadays many companies are basing their applications and solutions on
Tatiana Staffaroni
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. 
Denis Magda
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.