1-Relational Database
Highlight: Excellent for structured data and complex queries, ensuring data integrity.
Use Cases: Ideal for banking, CRM, and any scenario requiring strong ACID compliance.
Examples: MySQL, PostgreSQL, Oracle.
2-NoSQL Database
Highlight: Great for scalability and flexibility with unstructured data.
Use Cases: Suitable for big data analytics, real-time web apps, and content management.
Examples: MongoDB, Cassandra, Redis.
3-NewSQL Database
Highlight: Combines traditional RDBMS ACID compliance with the scalability of NoSQL.
Use Cases: Best for applications needing high transaction rates along with strong consistency, like financial trading platforms and high-speed retail systems.
Examples: Google Spanner, CockroachDB, VoltDB.
4-Document-Oriented Database
Highlight: Stores data in document formats, offering schema flexibility.
Use Cases: Best for content management systems, e-commerce platforms, and applications requiring frequent updates to the data structure.
Examples: MongoDB, CouchDB, Amazon DocumentDB.
5-Key-Value Database
Highlight: Simple, efficient, and designed for high-speed read and write operations.
Use Cases: Session management, caching, and scenarios where quick lookups are critical.
Examples: Redis, DynamoDB, Etcd.
6-Column-Oriented Database
Highlight: Optimized for reading and writing data in columns, enhancing analytics and query performance.
Use Cases: Big data processing, real-time analytics, and data warehousing.
Examples: Cassandra, HBase, Google Bigtable.
7-Object-Oriented Database
Highlight: Aligns closely with object-oriented programming concepts, storing data as objects.
Use Cases: Complex data models like CAD systems, AI applications, and simulation systems.
Examples: db4o, ObjectDB, Versant.
8-Time-Series Database
Highlight: Specialized in handling time-stamped data, efficient in querying time-based data.
Use Cases: IoT applications, financial services, and monitoring systems.
Examples: InfluxDB, TimescaleDB, Kdb+.
9-Wide-Column Store
Highlight: Combines elements of relational and NoSQL, efficient for storing large volumes of data.
-Data warehousing, big data processing, and real-time analytics.
Examples: Cassandra, Google Bigtable.
10-Spatial Database
Highlight: Specialized in storing and querying spatial information like maps and geographic locations.
-Ideal for geographic information systems (GIS), location-based services, and environmental modeling.
Examples: PostGIS (extension for PostgreSQL), Oracle Spatial
11-Graph Database
Highlight: Optimized for storing and navigating complex relationships between data points.
Use Cases: Social networks, recommendation engines, and fraud detection systems.
Examples: Neo4j, Amazon Neptune, OrientDB.
12-In-Memory Database
Highlight: Stores data in the main memory (RAM) for faster processing speeds.
Use Cases: High-performance applications like telecommunications, gaming, and real-time analytics.
Examples: Redis, MemSQL.