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 ...

NoSQL databases have surged in popularity as organizations struggle to serve highly distributed Web applications, but navigating the various types of NoSQL databases and the vendors providing them has ...

Document-oriented databases (also called: aggregate databases, document databases or document stores) place each record, and its associative data, inside single documents. This database type is a ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

“The right tool for the right job.” If such wisdom holds true anywhere, it certainly holds true with the choice of database a developer picks for a given application. Document databases, one of the ...

While relational databases rely on rigid structures, document databases are much more natural to work with and can be used for a variety of use cases across industries. A document database (also known ...

A document database is a type of nonrelational database that is designed to store and query data as JSON-like documents. Document databases make it easier for developers to store and query data in a ...

Looking to bolster query capabilities for its NoSQL database, Couchbase this week is trumpeting the arrival of its N1QL “next-generation” declarative query language, which brings SQL-like querying to ...

YugabyteDB extends distributed Postgres to support document database workloads, empowering developers to build next-generation apps with the consistency of a relational database, scale of document ...

Businesses and organizations are increasingly challenged to handle the huge volumes of data, both internally generated and acquired from outside sources, that they need to process, store and analyze ...