6 Database Types You Must Know
1. Relational Database
- Data Model: Organizes data into tables with rows and columns.
- Examples: MySQL, PostgreSQL, Oracle, SQL Server.
- Key Features: ACID compliance, strong data consistency, structured data storage, support for SQL queries, well-suited for complex transactions and reporting.
2. Document Database
- Data Model: Stores data in semi-structured or JSON-like documents.
- Examples: MongoDB, CouchDB, Firebase Firestore.
- Key Features: Flexible schema, horizontal scalability, support for semi-structured data, well-suited for content management systems and real-time applications.
3. In-Memory Database
- Data Model: Stores data entirely in the system's main memory (RAM).
- Examples: Redis, Memcached, Apache Ignite.
- Key Features: Ultra-fast data retrieval, low-latency, suitable for caching, session management, and real-time analytics.
4. Graph Database
- Data Model: Represents data as nodes and edges to model relationships.
- Examples: Neo4j, Amazon Neptune, ArangoDB.
- Key Features: Efficient querying of complex relationships, graph traversal, suitable for social networks, recommendation systems, and fraud detection.
5. Time-Series Database
- Data Model: Optimized for time-ordered data points, like sensor readings or log files.
- Examples: InfluxDB, Prometheus, TimescaleDB.
- Key Features: Efficient storage and retrieval of time-series data, aggregations, retention policies, ideal for monitoring, IoT, and event data.
6. Spatial Database
- Data Model: Designed for storing and querying spatial or geographic data.
- Examples: PostGIS (extension for PostgreSQL), MongoDB Geospatial, Microsoft SQL Server Spatial.
- Key Features: Geospatial indexing, support for spatial data types (points, polygons, lines), useful for location-based services, GIS (Geographic Information Systems), and map applications.
