There are a lot of databases out there in the market, lets understand the models types and the corresponding usage.
Different types of models used by databases
• Relational DBMS • Wide column stores • Content stores
• Document stores • Event stores • Graph DBMS
• Key-value stores • Multivalue DBMS • Native XML DBMS
• Navigational DBMS • Object Oriented DBMS • RDF Stores
• Search Engines
Relational databases: It is a collection of data items organized in set often called as tables. All the tables are related to each other. SQL statements are used to fetch, update, and delete the information from these tables.
Popular relational databases are
• Oracle • MySQL
• Microsoft SQL Server • PostgreSQL
Wide column stores: This type of databases stores data in a form of records with an ability to hold any number of dynamic columns. This type of databases doesn’t follow a specific schema. You can think of storing of the data in two-dimensional key-value.
Popular wide column stores databases are
• Cassandra • HBase • Accumulo
Content stores: They are also called as content repositories, specialized in management of digital content, such as text, pictures or videos, including their metadata. Some of the features included are full text search, versioning, hierarchical structured content, and access control.
Popular content stores databases are
• Jackrabbit • Modeshape
Document stores: They are also called as document oriented databases systems, and characterized by their schema-free organization of data. They store records and each record may have different columns. Document stores often use internal notations, which can be processed directly in applications, mostly JSON.
Popular document stores databases are
• MongoDB • CouchDB • Couchbase
Event stores: They persists all state changing events for an object together with a timestamp, thereby creating time series for individual objects. The current state of an object can be inferred by replaying all events for that object from time 0 till the current time.
Popular event stores are
• InfluxDB • Event Store
Graph DBMS: Graph DBMS, also called graph-oriented DBMS or graph database, represent data in graph structures as nodes and edges, which are relationships between nodes. They allow easy processing of data in that form, and simple calculation of specific properties of the graph, such as the number of steps needed to get from one node to another node.
Popular graph event database are
• Neo4j • Titan
Key-value stores: They can only store pairs of keys and values, as well as retrieve values when a key is known. One of the examples of the key-value stores is mentioned below
Popular Key-value stores are
• DynamoDB • Redis • Memcached
Multivalue DBMS: It is also called as multidimensional database. It is very similar to Relational databases, however it differ from relational databases in that they have features that supports to use of attributes of values, rather than all attributes being single-valued.
Popular Multivalue databases are
• Adabas • D3 • UniData,Universe • jBASE
Native XML DBMS: This type of databases internal data model corresponds to XML document. Native XML DBMS do not necessarily store data as XML documents, they can use other formats for better efficiency.
Generally defines a logical model for an XML document – as opposed to the data in that document – and stores and retrieves documents according to that model. Has an XML document as its fundamental unit of storage.
Popular Native XML DBMS
• MarkLogic • Sedna
Navigational DBMS: This type of databases allows access to data sets only via linked records. They were the first established systems able to manage large amounts of data.
Popular Navigational DBMS
• IMS • IDMS
Object Oriented DBMS: This type of databases stores the information in the form of objects as used in the object oriented programming. Object oriented databases are different from relational databases which are table oriented.
An object oriented DBMS follows an object oriented data model with classes (the schema of objects), properties and methods. An object is always managed as a whole. This means for example, that the insertion of an object, which in a relational system would probably be stored in multiple tables, will be performed automatically as one atomic transaction – without any action by the application program. Reading an object can also be done as a single operation and without complex joins.
There are tools and architectures that are now provided for the storage of objects into relational databases (such as Hibernate or JPA).
Popular object oriented databases are
• Cache • ObjectDB
RDF Stores: The Resource Description Framework (RDF) is a methodology for the description of information, originally developed for describing metadata of IT resources. Today it is used much more generally, often in connection with the sematic web, but also in other applications.
The RDF model represents information as triples in the form of subject-predicate-object.
Database management systems, which are able to store and process such triples, are called RDF stores or triple stores.
Popular RDF stores are
• AllegroGraph • Jena
Search Engines: Search engines are NoSQL database management systems dedicated to the search for data content. In addition to general optimization for this type of application, the specialization consists in typically offering the following features:
• Support for complex search expressions
• Full text search
• Stemming (reducing inflected words to their stem)
• Ranking and grouping of search results
• Geospatial search
• Distributed search for high scalability
Popular search engines are:
• Elasticsearch • Solr • Sphinx