DOCUMENT STORE Documents encapsulate and encode data (or information) in some standard formats or encodings. Different implementations offer different ways of organizing and/or grouping documents: Collections, Tags, Non-visible Metadata, Directory hierarchies.
DOCUMENT STORE Documents are addressed in the database via a unique key that represents that document. Retrieval of documents based on their contents. Examples: e. Xist, Apache Jackrabbit (JCR), Mongo. DB (BSON – binary JSON), Apache Couch. DB (JSON database).
GRAPH Elements interconnected with an undetermined number of relations between them. Any storage system that provides index-free adjacency. RDF databases. Examples: Oracle Spatial and Graph.
KEY–VALUE STORE Key–value stores allow the application to store its data in a schema-less way. The data could be stored in a datatype of a programming language or an object. There is no need for a fixed data model. Very fast access to data.
KEY–VALUE STORE Examples: Eventually‐consistent key‐value store: Apache Cassandra, Dynamo, Riak. Key–value cache in RAM: Redis, Velocity.
KEY–VALUE STORE Examples: Key–value stores on solid state or rotating disk: Mongo. DB, Oracle No. SQL Database, Big. Table. Ordered key–value stores: IBM Informix C-ISAM, Berkeley DB.
OBJECT DATABASE Information is represented in the form of objects as used in object -oriented programming. Database is integrated with the programming language – the programmer can maintain consistency within one environment. Examples: db 4 o