A data models define how the logical structure of a database is modeled. Data Models are fundamental entities to introduce abstraction in a Database Management Systems
(DBMS). According to WikiPedia, a database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated. The most popular example of a database model is the relational model, which uses a table-based format.
(Source: WikiPedia)
There are several database models or structures out there. To name few of the notable once include the following:-
- Hierarchical database model
- Network model
- Entity–relationship model
- Object model
- Document model
- Associative model
- Multidimensional model
- Multivalue model
- Semantic model
- XML database
- Named graph
- Triplestore
- Relational model
- Model-less (NoSQL) model - Big Data model
Databases technology have passed through several structural modelling in past decades to present days. From the decades of Hierarchical models to now what is known as NoSQL and Big Data databases model concepts.
However, the most relevant database models in today's contemporary data driven society are:
1) Relational model (RDBMS - Relational Database Management System)
2) NoSQL (Model-less) model - Big Data model
Examples the most relevant data model
Relational model
This technology is getting older and losing relevance. Some examples of Relational databases are: MS Access, SQLite, Oracle, MySQL, PostgreSQL, IBM DB2/Informix, and MsSQL server.
NoSQL and Big Data model
This technology is gaining ground fast especially in the in the contest of big databases that allows for high-performance, agile processing of information at massive scale. Some examples of NoSQL and Big Data databases are: Cassandra, Mongodb, CouchDB, Redis, Riak, RethinkDB, Couchbase (ex-Membase), Hypertable, ElasticSearch, Accumulo, VoltDB, Kyoto Tycoon, Scalaris, OrientDB, Aerospike, Neo4j, CodernityDB and Hadoop/HBase.
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