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Imagine a world without organized data – an inaccessible digital space where information flits from one corner to the next before disappearing into its depths. Now, picture an environment in which information flows smoothly and is easily accessible with just the tap of a keyboard – Database Management Systems (DBMS). Welcome to its amazing world.
All You Need To Know About Database Management System (DBMS)
A database management system (DBMS) is software designed to define, modify, retrieve, and manage database information. A DBMS typically handles manipulation of the actual data, such as format or field names within records or files, and sets rules for validating or manipulating such information. IBM first developed its Hierarchical Database System in the early 1960s.
Data are organized as parent-child nodes within this form of a database. Records contain their own and those of their parents and children – creating an elaborate tree-like structure. Parent-child relationships involve the attachment of records to each other through hierarchical databases that facilitate one-to-many relationships; however, such an approach is usually inflexible and cannot accommodate unexpected relationship changes over time.
Bank and telecom industries use network databases extensively to create high-performance applications and manage information management needs. Examples of network databases include IBM System for Information Management (IMS) and Windows Registry, while Charles Bachman invented network database architecture using network structures to form relationships between entities.
Network databases are commonly found on large computer networks. While similar to hierarchical databases, network databases differ by permitting one node to have relationships with multiple entities within its structure. Examples of databases include Integrated Data Store (IDS), IDMS, Raima Database Manager, TurboIMAGE, and Univac DMS-1100.
Relational Databases remain among the most widely used of all databases available today. Relational databases store data relating to relationships among records in a table with rows and columns representing records as rows and each attribute as columns, with each field representing value within data. Structured Query Language (SQL) is used to query these relational databases, including inserting, deleting, manipulating, and searching records.
Relational databases depict relationships among two or more tables using Key Fields as their connection mechanism. Each row in a relational database features its key field, which connects it to another table; examples of which include SQL Server, Oracle, MySQL, SQLite, and IBM DB2. In the early 1980s, object-oriented Databases were first developed.
They focused on object-oriented programming functionality to enhance C++ and Java semantics while providing additional database features. Furthermore, object-oriented Databases require advanced programming language objects. Provides full-featured database programming capability while remaining compatible with native languages, thus expanding functionality from database systems into object programming languages.
Example: Some Object-Oriented Databases have been designed to work with OOP languages like Delphi, Ruby, C++, Java, and Python. Examples of such a database include Tornado Gemstone InterSystems Cache Versant Object Database ODABA ZODB Poet, to name just a few. JADE, Informix, and…Graph Databases are NoSQL databases used for semantic queries using their graphical structure.
Data is typically organized as nodes, edges, properties representing records, links between nodes (edges), and additional information attached to each node (properties). Examples include Neo4j, Azure Cosmos DB, SAP HANA Sparksee OrientDB, and ArrangoDB MarkLogic, while some Relational Database Management Systems such as Oracle or SQL Server 2017 also support graph databases.
Peter Chen created the Entity-Relations Model Databases in 1976. Each row in a table represents one instance of an entity type, while each column represents its attributes. File Databases (DBs) are NoSQL databases that store key values in documents that allow access to related elements and data attributes. File DBs became increasingly popular because of this document storage method and NoSQL properties like faster search. Popular examples include Hadoop/Hbase/MapR/Amazon SimpleDB/Flink/ Azure DocumentDB and IBM Informix.