TYPES OF DATABASES

Databases come in different types, each designed for specific data management needs. Here’s a breakdown of the major categories:

1. Relational Databases (RDBMS)

• Structured with tables, rows, and columns.
• Uses SQL for querying and managing data.
• Examples: MySQL, PostgreSQL, Microsoft SQL Server, Oracle Database.

2. NoSQL Databases

• Flexible data structures like key-value pairs, documents, graphs, or wide-columns.
• Ideal for large-scale applications and real-time data.
• Examples:

• Document-based: MongoDB, CouchDB
• Key-value: Redis, DynamoDB
• Wide-column: Apache Cassandra, HBase
• Graph-based: Neo4j, ArangoDB

3. Cloud Databases

• Hosted and managed in cloud environments.
• Scalable and accessible from anywhere.
• Examples: Google Cloud Spanner, AWS RDS, Azure Cosmos DB.

4. In-Memory Databases

• Stores data in RAM for ultra-fast performance.
• Used for caching and real-time analytics.
• Examples: Redis, Memcached.

5. Time-Series Databases

• Optimized for handling time-stamped data.
• Used in monitoring systems, IoT, and financial analysis.
• Examples: InfluxDB, TimescaleDB.

6. Graph Databases

• Designed for data with relationships, like social networks.
• Examples: Neo4j, Amazon Neptune.

7. Object-Oriented Databases

• Stores data as objects instead of traditional tables.
• Used in AI and complex applications.
• Examples: ObjectDB, db4o.

8. Columnar Databases

• Organizes data by columns instead of rows for analytics and reporting.
• Examples: Apache HBase, Google Bigtable.

Each type has its strengths depending on scalability, structure, and speed.