With a document database, data is not stored in tables with distinct column types. Instead, it’s stored in freeform “documents” with any number of fields and any number of nested structures.

NoSQL databases can take a number of forms. They can be cloud services or install on-premises. They can support one or more data models: key-value, document, column, graph, and sometimes even ...

Because any database that does not support the SQL language is, by definition, a 'NoSQL' database, some very different databases coexist under the NoSQL banner. Massively scalable data stores like ...

Document store databases let you manage records that are long and have varied structure. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big ...

Other NoSQL databases are designed to be flexible, and focus on data models: they don’t enforce a rigid or consistent schema across stored data. These ‘document stores’ expand upon the traditional key ...

When a developer leverages a document database to support transactional workloads and persistence, they can store/retrieve data much faster. Transactional applications can store/retrieve data with as ...

Everywhere you look, there are new NoSQL databases — or “data stores,” if you’re one of those who feel that the word “database” can only be used by proper relational software offering ...

mongodb.com In MongoDB’s case, its document-based architecture NoSQL database allows users to store unstructured / semi-structured data in a flexible schema.

Given the rise in popularity of NoSQL functionality, SQL database vendors have taken notice and are implementing NoSQL-like functionality within their database structure.

This open-source, MIT-licensed document-oriented NoSQL database aims to provide a Postgres-based open standard for BSON data types.