Document-Oriented Database also called Document Store or Document Database. Document Database is a Database that stores information in documents. Document Databases are general-purpose Databases that can be used in a variety of use cases and industries. Document Databases are non-relational and one of the NoSQL databases. Document Databases are the most popular alternative to tabular, relational databases. Document Databases use flexible documents, instead of storing data in fixed rows and columns.
As per MongoDB, Document Databases have the following key features:
- Document Model: Data is stored in documents (unlike other databases that store Data in structures like tables or graphs). Documents map to objects in most popular programming languages, which allows developers to rapidly develop their applications.
- Flexible Schema: Document databases have a flexible schema, meaning that not all documents in a collection need to have the same fields. Note that some Document Databases support schema validation, so the schema can be optionally locked down.
- Distributed and Resilient: Document Databases are distributed, which allows for horizontal scaling (typically cheaper than vertical scaling) and data distribution. Document databases provide resiliency through replication.
- Querying through an API or Query Language: Document Databases have an API or Query Language that allows developers to execute required operations on the database. Developers have the ability to query for documents based on unique identifiers or field values.
Document-Oriented Database – Use Cases
- Catalog Information
- Users Profile
- Content Management
- Real-Time Big Data
