“NoSQL 101: Navigating the World of Non-Relational Databases”

Different type of NOSQL Databases

1. Key-value databases: These databases are the simplest form of NoSQL databases and are based on the key-value storage model, where data is stored in a hash table format, with a unique key that maps to a specific value. Key-value databases are highly scalable and provide fast data access, making them ideal for use cases such as caching, session management, and real-time analytics. Examples of key-value databases include Redis and Riak.
2. Document databases: These databases store data in the form of semi-structured documents, such as JSON or XML. Each document can have a different structure and fields, making it more flexible than table-based databases. Document databases are well suited for use cases such as content management, product catalogs, and user profiles. Examples of document databases include MongoDB and Couchbase.
3. Column-family databases: These databases store data in the form of columns instead of rows and are optimized for storing large amounts of data across multiple machines. Column-family databases are known for their high scalability and performance and are ideal for use cases such as real-time analytics, time-series data, and big data processing. Examples of column-family databases include Apache Cassandra and Hbase.
4. Graph databases: These databases store data in the form of nodes and edges, which represent entities and their relationships. Graph databases are optimized for handling complex, highly connected data and are ideal for use cases such as social networks, recommendation systems, and fraud detection. Examples of graph databases include Neo4j and Amazon Neptune.
5. Time-series databases: These databases are optimized for handling time-stamped data and are used for monitoring, logging, and IoT use cases. Time-series databases are designed to handle high-frequency data streams, and to perform analytics on that data. Examples of time-series databases include InfluxDB and OpenTSDB.
6. Object databases: These databases store data in the form of objects, which are instances of a class, rather than in tables as in relational databases. Object databases are well suited for use cases such as complex data modeling, and are often used in combination with object-oriented programming languages. Examples of object databases include db4o and ZopeDB
7. Search Engine databases: These databases are optimized for search and text retrieval use cases, such as Elasticsearch and Solr. They are built on top of Lucene and provide a distributed search engine, with a wide range of text-processing capabilities, they are used in many use cases such as website search, e-commerce product search, log analysis and more.