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Graph databases are designed for data whose relations are well represented as a graph consisting of elements connected by a finite number of relations. Examples of data include social relations, public transport links, road maps, network topologies, etc. Graph databases and their query language
Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
A document-oriented database is a specialized key-value store, which itself is another NoSQL database category. In a simple key-value store, the document content is opaque. A document-oriented database provides APIs or a query/update language that exposes the ability to query or update based on the internal structure in the document. This ...
In analogy with relational databases, a standard column family is as a "table", each key–value pair being a "row". [1] Each column is a tuple consisting of a column name, a value, and a timestamp. [2] In a relational database table, this data would be grouped together within a table with other non-related data. [3]
It is designed to provide high availability, scalability, and low-latency access to data for modern applications. Unlike traditional relational databases, Cosmos DB is a NoSQL (meaning "Not only SQL", rather than "zero SQL") and vector database, [1] which means it can handle unstructured, semi-structured, structured, and vector data types. [2]
General purpose database that has high data processing speeds in main-memory alone. It comes with high-availability, replication and scalability features; three interfaces (including Direct Access Mode and Direct Access API Mode) as well as conventional client/server protocols such as TCP/IP and IPC for more complex database operations.
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. A wide-column store can be interpreted as a two-dimensional key–value store. [1] Google's Bigtable is one of the prototypical examples of a wide-column store. [2]
NoSQL databases like document databases typically does not conform to the relational view. For example, an JSON or XML database might support duplicate records and intrinsic ordering. Such database can be described as non-relational. But there are also database models which support the relational view, but does not embrace first normal form. [4]