Use Cases: Big data analytics, IoT sensor data, real-time logging, large-scale messaging systems.
Examples: Apache Cassandra, HBase, ScyllaDB.
Why Special: Built for extreme horizontal scalability and high availability, crucial for applications generating continuous streams of data.
4. Graph Databases:
Concept: Store data as nodes (entities) and edges (relationships between entities), making connections first-class citizens. Optimized for traversing and querying complex relationships rapidly.
Use Cases: Social networks (friend connections), recommendation engines (product-to-product relationships), fraud detection (identifying unusual connections), knowledge graphs.
Examples: Neo4j, Amazon Neptune, ArangoDB.
Why Special: Excel where the relationships between data points chinese overseas british data are as important as the data itself, offering unparalleled performance for connected data analysis.
5. Time Series Databases:
Concept: optimizing for high ingest rates, range queries, and aggregations over time.
Use Cases: IoT sensor data, financial market data, application monitoring, industrial control systems.
Examples: InfluxDB, TimescaleDB (relational extension), Prometheus.
Why Special: Tailored for the unique characteristics of temporal data, enabling efficient storage and rapid analysis of trends and patterns over time.
6. Geospatial Databases:
Concept: Optimized for storing and querying geographical or spatial data, including points, lines, and polygons, and performing spatial operations (e.g., "find all points within a 5km radius").
Use Cases: Location-based services, logistics, urban planning, environmental monitoring.