Fast-changing data needs a fast computing architecture.
Analytics used to exclusively depend on a data warehouse and time-consuming extract, transform, and load methods that could take hours or days.
Today, however, businesses need to analyze a massive amount of real-time data for applications such as stock trading, ecommerce, and the Internet of Things. Increasingly they are turning to compute architectures that allow analysis of that data within seconds.
One technology attracting attention is the in-memory data grid. IMDGs often complement traditional databases, but have unique characteristics (such as use of a “NoSQL” key-value store) that make them well-suited to handle fast-changing data.
In this white paper from ScaleOut Software, here’s what you will learn:
- The difference between operational intelligence and streaming analytics or event-processing systems.
- How object-oriented, in-memory data storage offers the ability to rapidly capture data changes and scale to meet data needs.
- How IMDGs employ data-parallel programming to reduce compute times and provide fast analysis.
To get a free copy of the white paper, please fill the form.
