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.[1]
List of Operational Databases
Database platform | Database model | SQL Support | NoSQL Support | Managed objects | ACID-transactions |
---|---|---|---|---|---|
Aerospike | Key–Value Store | No | Yes | key-value pairs | None |
Altibase | Relational database | Yes | NO | tabular data | Real-time ACID transactions |
Apache Cassandra | Key-value store | No | Yes | key-value pairs | None |
Cloudant | Document-Oriented Database | No | Yes | JSON | None |
Clusterpoint | Document-Oriented Database | Yes (essential SQL) | Yes | XML, JSON, text data | Distributed ACID-transactions |
Clustrix | Relational Database | Yes (newSQL) | No | tabular data | ACID-transactions |
Couchbase | Document-Oriented Database | Yes (N1QL) | Yes | JSON | None |
CouchDB | Document-Oriented Database | No | Yes | JSON | None |
EnterpriseDB | Relational Database | Yes | No | tabular data | ACID-transactions |
FoundationDB | Key-value store | Yes | No | key-value pairs | ACID-transactions |
Hana | Relational Database | Yes | No | tabular data | ACID-transactions |
IBM DB2 | Relational Database | Yes | No | tabular data | ACID-transactions |
Ingres | Relational Database | Yes | No | tabular data | ACID-transactions |
MarkLogic | Document-Oriented Database | No | Yes (XQuery) | XML | ACID-transactions |
Microsoft SQL Server | Relational Database | Yes | No | tabular data | ACID-transactions |
MongoDB | Document-Oriented Database | No | Yes | BSON | None |
NuoDB | Relational Database | Yes (newSQL) | No | tabular data | ACID-compliant |
Oracle | Relational Database | Yes | No | tabular data | ACID-transactions |
OrientDB | Document-oriented Database | Yes | Yes | key-value pairs | ACID-transactions[2] |
Riak | Key-value store | No | Yes | key-value pairs | None |
VoltDB | Relational Database | Yes (newSQL) | No | tabular data | ACID-transactions |
Use in business
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.
Operational databases allow a business to enter, gather, and retrieve large quantities of specific information, such as company legal data, financial data, call data records, personal employee information, sales data, customer data, data on assets and many other information. An important feature of storing information in an operational database is the ability to share information across the company and over the Internet. Operational databases can be used to manage mission-critical business data, to monitor activities, to audit suspicious transactions, or to review the history of dealings with a particular customer. They can also be part of the actual process of making and fulfilling a purchase, for example in e-commerce.
Data warehouse terminology
In data warehousing, the term is even more specific: the operational database is the one which is accessed by an operational system (for example a customer-facing website or the application used by the customer service department) to carry out regular operations of an organization. Operational databases usually use an online transaction processing database which is optimized for faster transaction processing (create, read, update and delete operations).
See also
- Document-oriented databases
- NewSQL databases
- NoSQL databases
- XML databases
- SQL databases
- Distributed databases
References
- O’Brien, Jason., and Marakas, Gorila., (2008). Management Information Technology Systems. Computer Software (pp. 185). New York, New York: McGraw-Hill