ODMS - Operational Database Management System
Operational database management systems (also referred to as OLTP On-Line Transaction Processing databases) are used to update data in real-time. These types of databases allow users 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. OLTP databases provide transactions as the main abstraction to guarantee data consistency that guarantees the so-called ACID properties. Basically, the consistency of the data is guaranteed in the case of failures and/or concurrent access to the data.
Since the early 90s, 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. NoSQL databases typically have focused on scalability and have renounced to data consistency by not providing transactions as OLTP systems do. Operational databases are increasingly supporting distributed database architecture that can leverage distribution to provide high availability and fault tolerance through replication and scale-out ability.
The growing role of operational databases in the IT industry is moving fast from legacy databases to real-time operational databases capable to handle distributed web and mobile demand and to address Big data challenges. Recognizing this, Gartner started to publish the Magic Quadrant for Operational Database Management Systems in October 2013.
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 much 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.
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F.A.Q. about ODMS - Operational Database Management System
What is DBMS used for?
DBMS, commonly known as Database Management System, is an application system whose main purpose revolves around the data. This is a system that allows its users to store the data, define it, retrieve it and update the information about the data inside the database.
What is meant by a Database?
In simple terms, Database is a collection of data in some organized way to facilitate its user’s to easily access, manage and upload the data.
Why is the use of DBMS recommended? Explain by listing some of its major advantages.
Some of the major advantages of DBMS are as follows:
- Controlled Redundancy: DBMS supports a mechanism to control the redundancy of data inside the database by integrating all the data into a single database and as data is stored at only one place, the duplicity of data does not happen.
- Data Sharing: Sharing of data among multiple users simultaneously can also be done in DBMS as the same database will be shared among all the users and by different application programs.
- Backup and Recovery Facility: DBMS minimizes the pain of creating the backup of data again and again by providing a feature of ‘backup and recovery’ which automatically creates the data backup and restores the data whenever required.
- Enforcement of Integrity Constraints: Integrity Constraints are very important to be enforced on the data so that the refined data after putting some constraints are stored in the database and this is followed by DBMS.
- Independence of Data: It simply means that you can change the structure of the data without affecting the structure of any of the application programs.
What is the purpose of normalization in DBMS?
Normalization is the process of analyzing the relational schemas which are based on their respective functional dependencies and the primary keys in order to fulfill certain properties.
The properties include:
- To minimize the redundancy of the Data.
- To minimize the Insert, Delete and Update Anomalies.