These databases store data in flexible

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Types of Special Databases
The landscape of special databases is broad. Here are some of the most common categories and the problems they solve:

1. Time-Series Databases
Use case: Monitoring, IoT, financial trading
Examples: InfluxDB, TimescaleDB, Prometheus

Time-series databases are designed for data points that are indexed over time. They’re optimized for high-ingestion rates and fast aggregation queries like “average CPU usage in the last hour.”

2. Graph Databases
Use case: Relationship mapping, fraud detection
Examples: Neo4j, ArangoDB, Amazon Neptune

Graph databases store data as nodes and truemoney data edges, which makes them ideal for understanding how entities are connected. They outperform relational databases in complex relationship queries.

3. Document Databases
Use case: CMS, e-commerce catalogs, mobile apps
Examples: MongoDB, Couchbase

JSON-like documents. They’re schema-less, allowing for rapid development and easy evolution of the data model.

4. Ledger Databases
Use case: Finance, legal records, compliance
Examples: Amazon QLDB, Hyperledger Fabric

Ledger databases ensure an immutable and cryptographically verifiable log of all transactions. Perfect for auditing and compliance-heavy environments.

5. Geospatial Databases
Use case: Mapping, real-time tracking, logistics
Examples: PostGIS (extension of PostgreSQL), Google BigQuery GIS

They allow you to store, query, and analyze spatial data like GPS coordinates and boundaries, critical for industries like delivery, urban planning, or fleet management.