The Brains of RapidResponse: In-Memory, High-Speed, Big Data
At the heart of RapidResponse® is a proprietary in-memory database with integrated and optimized analytics that can process millions of records of data and perform demanding calculations in seconds.
The scalable in-memory computing engine of RapidResponse has the ability to mimic any data model to create ERP agnostic analytics. One system can simultaneously model and imitate the analytics of multiple ERP systems and other transactional applications coming from multiple enterprises. It is this technology breakthrough that enables our customers to continuously expand the relevant application areas of RapidResponse across their businesses.
RapidResponse uses a proprietary in-memory database, which relies on main memory for computer data storage, as opposed to the more common, slower database management systems that employ disk storage.
In addition to the RapidResponse in-memory database, RapidResponse also has a proprietary engine for scenario creation ("what-if" analysis). This creates the ability for anyone to simulate anything, anytime. At the root of response management, is the ability to test the impact of various course correction alternatives. With RapidResponse, creating scenarios take a fraction of a second, regardless of how large your dataset is. Scenarios can be kept private, or shared with individuals, or teams, for the purpose of collaborating. Once created, all scenarios are available for viewing, scorecard comparison, and analysis… simultaneously.
Invisible to you, analytics are embedded directly within the RapidResponse engine, and unlike batch-oriented systems, they are "always-on". Like a human brain, RapidResponse knows when things change, and can automatically compute the impact in real-time. It is always ready to answer your next question.
Further, RapidResponse uses a site construct to contain specific analytic behavior; thus allowing for a single instance of RapidResponse to support multi-enterprise networks, where each node is driven by their own unique analytics (e.g. Site 1 behaves like SAP, Site 2 behaves like Oracle, etc). Each site in the network can represent any purpose (e.g. Inventory Hub, Distribution, Warehouse, Customer location, Supplier, etc). The result is instant and accurate impact analysis and the ability to identify the full impact of decisions prior to execution.