inMemory+ is a database management system that primarily relies on computerís main memory for data storage. It outperforms conventional databases because in-memory databases are faster than disk-optimized databases since the internal optimization algorithms are simpler and execute fewer CPU instructions. Accessing data in memory eliminates seek time when querying the data, which provides faster and more predictable performance than disk-based databases.
inMemory+ is a distributed in-memory database that delivers real-time analytics for Big Data. Five or six years ago, analysts working with big datasets made queries and got the results back overnight. The data world was revolutionized a few years ago when Hadoop and other tools made it possible to get the results from queries in minutes. Today analysts demand query results in seconds, near real-time. inMemory+ delivers on those demands.
inMemory+ uses a distributed computing architecture. It involves the roles of Master and Slave Nodes. The Master Node is primarily responsible for data distribution and accumulating the query results. Slave Nodes are the data carrier on which actual data resides. Its shared-nothing architecture is highly scalable using commodity hardware in which each node is independent and self-sufficient and there is no single point of contention across the system and none of the nodes share memory or disk storage.
As seasoned data-science professionals, we developed inMemory+ to help other big data and business intelligence professionals better illustrate their findings. Now you can display your findings more succinctly by presenting your data in a clear and easy to understand methods. Enable powerful analytics, dashboards, and charts that are instantly populated and constantly updated with current data, revealing the full progression of data driven results overtime. Your hard work deserves to be presented in a way that tells the entire data story. inMemory+ arms you with the right imagery to help your clients make better more informed decisions quickly.