The GridGain Systems In-Memory Computing Blog
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. Moreover, Ignite can import database schemas and automatically generate all the…
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.
Distributed in-memory computing systems such as Apache Ignite can be used to improve the performance and scalability of data-driven applications. Distributed systems, though, depend…
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…
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…
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…
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.
Detecting fraud requires complex data…
Introduction
Nowadays many companies are basing their applications and solutions on microservices architecture. One of the main benefits of this approach is that it allows splitting a solution into a number of loosely coupled software components (microservices). These software components might have their own release and life cycles, and even development teams. Moreover, these…
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…
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…
When it comes to querying and acting on data — including in Big Data/Fast Data environments — SQL still dominates. And no other database-agnostic in-memory solution handles SQL functionality like the Apache Ignite In-Memory Data Fabric.Join us at 10:00 AM PT on Wednesday, March 23rd as Nikita Ivanov, CTO of GridGain Systems and member of the Project Management Committee for Apache® Ignite™,…