1. Document stores:

•Document-based NOSQL systems store data as collections of similar documents.

• Resemble complex objects

• Do not require to specify a schema, but are specified as self-describing data

• Each document can have different data elements (attributes)

• Can be specified in various formats, such as XML or JSON (JavaScript Object Notation)

• Are accessible via their document id

Examples: Mongo DB

2. Key-value stores:

• Every data item (value) must be associated with a unique key

• Retrieving the value by supplying the key must be very fast

• Value-

1. Can have very different formats for different key-value storage systems:

2. String / array of bytes: the application using the key-value store has to interpret the structure of the data value

3. Structured data rows (tuples) similar to relational data

4. Semi structured data using a self-describing data format

Example: Amazon Dynamo DB, Project Voldemort

3. Wide column stores:

A wide column store is a type of key-value database. It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table.

Working Principle-

• Vertical partitioning – tables are partitioned by column into column families

• Each column family is stored in its own files

• Versioning of data values is allowed

• The key is multidimensional (in contrast to key-value stores)

Examples: Google distributed storage system (BigTable), Apache Hbase

4. Graph-Databases:

Data is organized as a graph, which is a collection of nodes, relationships, and properties.

Node-

• Can contain properties

• Can contain labels, which groups nodes with the same label into subsets for querying purposes

Relationship-

• Is directed, each relationship has a start node and an end node

• Can contain properties

• Has a relationship type, which helps to identify similar relationship types for querying purposes

Properties-

Store the data items associated with nodes and relationships as list of key-value pairs

Example: Neo4j

5. Hybrid Systems:

Hybrid SQL‐NoSQL database solutions combine the advantage of being compatible with many SQL applications and providing the scalability of NoSQL ones.

Example: Xeround