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Transcript
NOSQL
Implementation and examples
Maciej Matuszewski
QUERYING
 RESTful interfaces,
 SQL, SQL2 (JCR),
 Query by example,
 SPARQL (RDF Query Language),
 UnQL (Unstructured Query Language),
 XQuery, XPath,
 Other.
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:
 eXist,
 Apache Jackrabbit (JCR),
 MongoDB (BSON – binary JSON),
 Apache CouchDB (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:
 MongoDB,
 Oracle NoSQL Database,
 BigTable.
 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:
 db4o