1. Relational Databases
- Examples: Postgres, MySQL, Oracle
- Features: Organized into tables with fixed columns; uses foreign keys to establish relationships.
- Use Cases: E-commerce, finance, healthcare, and applications with structured data and well-defined relationships.
2. Wide-Column Databases
- Examples: Cassandra, ScyllaDB, DynamoDB
- Features: NoSQL databases with flexible columns that can vary across rows; optimized for high scalability and low-latency querying.
- Use Cases: Big data, analytics, high-write throughput.
3. Time-Series Databases (TSDB)
- Examples: InfluxDB, Prometheus, Kdb+
- Features: Optimized for time-indexed data like metrics and events.
- Use Cases: Financial trading, performance monitoring, IoT sensor data.
4. Ledger Databases
- Examples: Amazon Quantum
- Features: Designed for financial data with immutability and cryptographic verification; validated by a central authority.
- Use Cases: Financial applications, supply chain management, voting systems.
5. Graph Databases
- Examples: Neo4j, ArangoDB, Amazon Neptune
- Features: Store data as nodes, relationships, and properties; ideal for managing interconnected data.
- Use Cases: Social networks, knowledge graphs, recommendation systems.
6. Object-Oriented Databases (ODBMS)
- Examples: ObjectDB, db4o
- Features: Store data as objects, similar to object-oriented programming languages; support inheritance and polymorphism.
- Use Cases: Object-oriented applications, multimedia databases.
7. Hierarchical Databases
- Examples: IBM IMS, Windows Registry
- Features: Organize data in a tree-like structure with parent-child relationships.
- Use Cases: File systems, legacy systems.
8. Document Databases
- Examples: MongoDB, CouchDB, ArangoDB
- Features: Store semi-structured data as JSON-like documents; flexible and hierarchical.
- Use Cases: Content management systems, e-commerce platforms.
9. Key-Value Databases
- Examples: Redis, Couchbase, DataStax
- Features: Store data in key-value pairs; highly scalable and fast.
- Use Cases: Caching, session storage.
10. Blob Databases
- Examples: Amazon S3
- Features: Store large unstructured binary data like media files.
- Use Cases: Multimedia storage, content delivery networks.
11. In-Memory Databases
- Examples: Redis, Memcached, Apache Ignite
- Features: Store data in memory for ultra-low latency and high throughput.
- Use Cases: Caching, real-time bidding, gaming leaderboards.
12. Text Search Databases
- Examples: Elasticsearch
- Features: Optimized for storage, retrieval, and analysis of large volumes of text data.
- Use Cases: Web searches, auto-complete, filtering.
13. Spatial Databases
- Examples: PostGIS, Oracle Spatial
- Features: Manage spatial data types (e.g., points, polygons) and related relationships.
- Use Cases: GIS, location-based services, spatial analysis.
14. Vector Databases
- Examples: Pinecone, Chroma
- Features: Store, index, and search high-dimensional data; optimized for AI and machine learning tasks.
- Use Cases: Image and video search, recommendation systems, AI model embeddings.
15. Embedded Databases
- Examples: SQLite, RocksDB, BerkeleyDB
- Features: Lightweight databases integrated within applications; offer fast data access with a small footprint.
- Use Cases: Desktop applications, quick proofs of concept, resource-constrained environments.
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