A non-relational database describes a database with flexible storage and retrieval. While NoSQL databases form a subset of non-relational databases, non-relational databases also encompass any system that deals with high volumes of unstructured data at a lower cost. Many non-relational databases support SQL-compatible queries too. Data lakes and cloud databases can also be considered non-relational databases. Non-relational databases have existed before NoSQL became common.
Other Definitions of a Non-Relational Database Include:
- “A mechanism for storage and retrieval of data that employs less constrained consistency models than traditional relational databases.” (DAMA International)
- A database, also known as “NoSQL, that can translate strange data quickly and avoid the rigidity of SQL by replacing ‘organized’ storage with more flexibility.” (Keith Foote)
- “A technology that handles very large, unstructured data volumes with a low cost of storage processing.” (Gartner)
- A database that uses a storage model that is optimized for the specific requirements of the type of data being stored. “For example, data may be stored as simple key/value pairs, as JSON documents, or as a graph consisting of edges and vertices.” (GitHub)
- “A database with a more flexible schema.” (TechRepublic)
Non-Relational Database Use Cases Include:
- A company uses a graph database to prevent fraud.
- The Massachusetts General Hospital Utility Multi-Programming System (MUMPS) “is a key-value store, and is able to store data in a schema-less fashion, which is handy for less-structured clinical data that a hospital may need to store.”
- A business sets up a data lake to hold “non-relational data from mobile apps, IoT devices, and social media.”
Businesses Use Non-Relational Databases to:
- Handle large volumes of unstructured data
- Manage different data storage needs
- Get better data performance
- Develop software solutions more easily
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