An in-memory database (IMDB, also known as a main memory database or MMDB) is a database whose data is stored in main memory to facilitate faster response times. Source data is loaded into system memory in a compressed, non-relational format. In-memory databases streamline the work involved in processing queries.
An IMDB is one type of analytic database, which is a read-only system that stores historical data on metrics for business intelligence/business analytics (BI/BA) applications, typically as part of a data warehouse or data mart. These systems allow users to run queries and reports on the information contained, which is regularly updated to incorporate recent transaction data from an organization’s operational systems.
In addition to providing extremely fast query response times, in-memory analytics can reduce or eliminate the need for data indexing and storing pre-aggregated data in OLAP cubes or aggregate tables. This capacity reduces IT costs and allows faster implementation of BI/BA applications.
Three developments in recent years have made in-memory analytics increasingly feasible: 64-bit computing, multi-core servers and lower RAM prices.
See also: big data analytics, association rules (in data mining), ad hoc analysis, unstructured data, data scientist, noisy data, descriptive modeling, opinion mining -sentiment mining, deep analytics
Expert Craig S. Mullins provides an in-depth overview of the pros and cons of the in-memory DBMS.