- Store data in tables with rows and columns - Enforce relationships between data using primary and foreign keys - Examples: MySQL, PostgreSQL, Oracle
NoSQL Databases
- Store data in non-relational formats - Designed for scalability and high performance - Types include: - Key-value stores (e.g., Redis, DynamoDB) - Document stores (e.g., MongoDB, CouchDB) - Graph databases (e.g., Neo4j, Titan) - Time-series databases (e.g., InfluxDB, Prometheus) - Wide-column stores (e.g., Cassandra, HBase)
In-memory Databases
- Store data in memory for faster access - Trade off durability for performance - Examples: Redis, Memcached
Object-Oriented Databases
- Store data as objects that encapsulate data and behavior - Focus on modeling real-world entities and relationships - Examples: Objectivity/DB, GemStone/S
Hierarchical Databases
- Store data in a tree-like structure where each node can have multiple child nodes - Examples: IMS, VSAM
Network Databases
- Store data in a network-like structure where records are connected by links - Focus on representing complex relationships between data - Examples: CODASYL, IDMS
Multidimensional Databases
- Store data in a multidimensional array - Designed for analyzing large amounts of data with multiple dimensions - Examples: Oracle Hyperion Essbase, Microsoft Power BI
Distributed Databases
- Store data across multiple computers or geographical locations - Designed for scalability and fault tolerance - Examples: Spanner, CockroachDB