Examples of RDBMS and NoSQL Databases

This article presents several common relational database management systems (RDBMSs) and NoSQL databases.


For an introduction to RDBMSs and NoSQL databases, see Properties of RDBMSs and NoSQL databases.

Popular relational databases and RDBMSs

The following list describes popular SQL and RDBMS databases:

  • Oracle®: An object-relational database management system (DBMS) written in the C++ language.

  • IBM DB2®: A family of database server products from IBM®.

  • SAP ASE®: A business relational database server product for primarily Unix® operating systems.

  • Microsoft SQL Server®: An RDBMS for enterprise-level databases that supports both SQL and NoSQL architectures.

  • Maria DB®: An enhanced, drop-in version of MySQL®.

  • PostgreSQL®: An enterprise-level, object-relational DBMS that uses procedural languages, such as Perl and Python, in addition to SQL-level code.

Popular NoSQL databases

The following list describes popular NoSQL databases:

  • MongoDB®: The most popular open-source NoSQL system. MongoDB is a document-oriented database that stores JSON-like documents in dynamic schemas.

  • Apache CouchDB®: An open-source, web-oriented database developed by Apache®. CouchDB uses the JSON data exchange format to store its documents; JavaScript for indexing, combining, and transforming documents; and HTTP for its API.

  • Apache HBase®: An open-source Apache project developed as a part of Hadoop®. HBase is a column store database written in Java with capabilities similar to those that Google BigTable® provides.

  • Oracle NoSQL Database®: A proprietary database that supports JSON table and key-value datatypes running on-premise or as a cloud service.

  • Apache Cassandra DB®: A distributed database that excels at handling extremely large amounts of structured data. Cassandra DB is also highly scalable. Facebook® created Cassandra DB.

  • Riak®: An open-source, key-value store database written in Erlang. Riak has built-in fault-tolerance replication and automatic data distribution that enable it to offer excellent performance.

  • Objectivity InfiniteGraph®: A highly specialized graph database that focuses on graph data structures. InfiniteGraph, implemented in Java, is useful for finding hidden relationships in big data.

Next step

Introduction to MongoDB

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