Operational database

Operational database management systems (also referred to as OLTP On Line Transaction Processing databases), are used to manage dynamic data in real-time. These types of databases allow you to do more than simply view archived data. Operational databases allow you to modify that data (add, change or delete data), doing it in real-time.

Since the early 90's, the operational database software market has been largely taken over by SQL engines. Today, the operational DBMS market (formerly OLTP) is evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases. Operational databases are increasingly supporting distributed database architecture that provides high availability and fault tolerance through replication and scale out ability.

Recognizing the growing role of operational databases in the IT industry that is fast moving from legacy databases to real-time operational databases capable to handle distributed web and mobile demand and to address Big data challenges, in October 2013 Gartner started to publish the Magic Quadrant for Operational Database Management Systems.

Operational databases are used to store, manage and track real-time business information. For example, a company might have an operational database used to track warehouse/stock quantities. As customers order products from an online web store, an operational database can be used to keep track of how many items have been sold and when the company will need to reorder stock. An operational database stores information about the activities of an organization, for example customer relationship management transactions or financial operations, in a computer database.

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