A:
Relational DB - MySQL, PostgreSQL:
Relational databases like MySQL and PostgreSQL use structured tables with predefined schemas, making them ideal for handling complex queries and transactions. They ensure data integrity through ACID properties and are widely used for applications requiring robust, relational data models.
NoSQL DB - MongoDB:
MongoDB is a NoSQL database that stores data in flexible, JSON-like documents, allowing for dynamic schemas. It's highly scalable and ideal for handling large volumes of unstructured or semi-structured data, making it popular for modern web applications.
In-memory DB - Redis:
Redis is an in-memory database known for its high-speed data processing capabilities. It supports various data structures like strings, hashes, and lists, making it suitable for caching, real-time analytics, and message brokering.
Distributed SQL DB - CockroachDB:
CockroachDB is a distributed SQL database designed to scale horizontally across multiple nodes while providing strong consistency and ACID transactions. It's ideal for applications requiring high availability and resilience across different geographic locations.
Time Series DB - InfluxDB:
InfluxDB is a time series database optimized for handling high write and query loads, particularly for time-stamped data. It's commonly used for monitoring, real-time analytics, and IoT applications where time-based data is crucial.
OO DB - db4o:
db4o is an object-oriented database that stores data as objects, closely aligning with object-oriented programming languages. It simplifies development by allowing direct storage and retrieval of objects without the need for conversion to relational tables.
Graph DB - Neo4j:
Neo4j is a graph database that excels at handling complex relationships between data entities. It uses a graph structure with nodes, relationships, and properties, making it ideal for applications like social networks, recommendation engines, and fraud detection.
Hierarchical DB - IBM IMS:
IBM IMS is a hierarchical database that organizes data in a tree-like structure with parent-child relationships. It's used primarily in legacy systems for high-performance transaction processing and is known for its reliability in handling large-scale, mission-critical applications.
Network DB - IDMS:
IDMS (Integrated Database Management System) is a network database that represents data using a graph of record types and set relationships. It allows more complex relationships than hierarchical databases and is often used in legacy systems requiring high performance.
Cloud DB - Amazon RDS:
Amazon RDS (Relational Database Service) is a managed cloud database service that supports multiple relational database engines, including MySQL, PostgreSQL, and Oracle. It automates tasks like backups, patching, and scaling, making it easy to deploy and manage databases in the cloud.
Most commonly used databases are :