Types of Databases

Relational Databases (RDBMS)

Relational databases store data in tables with rows and columns. They use Structured Query Language (SQL) for defining and manipulating data. Popular examples include MySQL, PostgreSQL, and Oracle.

NoSQL Databases

NoSQL databases are designed to handle large volumes of data that may not fit well into tables. They are categorized into document, key-value, column-family, and graph databases. Examples include MongoDB, Cassandra, and Redis.

Object-Oriented Databases

These databases store data in objects, similar to object-oriented programming languages. They support complex data types and relationships. Examples include db4o and ObjectDB.

Graph Databases

Graph databases store data in nodes and edges, making them ideal for representing complex relationships. Neo4j is a well-known graph database.

Distributed Databases

Distributed databases store data across multiple physical locations. They provide high availability and fault tolerance. Examples include Apache Cassandra and Google Spanner.

Cloud Databases

Cloud databases are hosted on cloud computing platforms, offering scalability and flexibility. Services like Amazon RDS and Microsoft Azure SQL Database are popular choices.

In-Memory Databases

In-memory databases store data in the main memory rather than on disk, providing faster access times. Redis and SAP HANA are examples of in-memory databases.

NewSQL Databases

NewSQL databases combine the scalability of NoSQL systems with the ACID guarantees of traditional RDBMS solutions. Examples include Google Spanner and CockroachDB.

Time-Series Databases

These databases are optimized for time-stamped or time-series data. They are used for monitoring, analytics, and IoT applications. InfluxDB is a popular time-series database.

Columnar Databases

Columnar databases store data in columns rather than rows, making them efficient for analytical queries. Apache HBase and Amazon Redshift are examples.