GridGain® Systems offers a variety of in-memory computing resources which include information on the GridGain in-memory computing platform and Apache Ignite™. Use the search fields below to identify the best resources for your needs or browse our extensive library of webinars, white papers and more using the navigation to the left.
The need for real-time computing has resulted in the growth of many different in-memory computing technologies including caches, in-memory data grids, in-memory databases, streaming technologies and broader in-memory computing platforms. But what are the best technologies for each type of project? Learn about your options from one of the leading in-memory computing veterans.
It used to be that the only way to improve application performance was to add a cache. But caches like Redis don't understand SQL. They require you to modify your applications with non-SQL coding and data models, and copy and synch data across two different models. They don't support ACID transactions very well. And they have their limits when it comes to scalability.
Many financial services companies are finding in-memory computing platforms such as GridGain and Apache Ignite to be a key strategy for meeting big data and real-time analytic challenges caused by High-Frequency Trading, Fraud Prevention, and Real-Time Regulatory Compliance
The GridGain in-memory computing platform, built on Apache® Ignite™ , enables high-performance transactions, real-time streaming, and fast analytics in a single, comprehensive data access and processing layer. This white paper covers the architecture, key capabilities and features of GridGain, and its integrations with Apache® Spark™ and Apache® Cassandra™.