Time-Series Databases

Specialized databases optimized for time-stamped data, metrics, and real-time analytics

What Are Time-Series Databases?

Time-series databases are optimized for handling data points indexed by time. They excel at ingesting, storing, and querying massive volumes of timestamped data with high write throughput and efficient compression.

Every data point includes a timestamp, making these databases perfect for monitoring, IoT sensors, financial tick data, and application metrics.

Popular Time-Series Databases

InfluxDB

Purpose-built for time-series data with built-in HTTP API, SQL-like query language, and excellent compression.

Best for: DevOps monitoring, IoT applications, real-time analytics

TimescaleDB

PostgreSQL extension combining relational database features with time-series optimizations. Full SQL support.

Best for: SQL-familiar teams, complex queries, hybrid workloads

Prometheus

Open-source monitoring system with time-series database. Ideal for metrics and alerting with powerful PromQL.

Best for: Kubernetes monitoring, application metrics, alerting

Amazon Timestream

Fully managed time-series database with automatic scaling and built-in analytics functions.

Best for: AWS environments, serverless applications, IoT

Common Use Cases

  • ✓Infrastructure Monitoring: Server metrics, CPU, memory, network
  • ✓IoT & Sensor Data: Temperature, pressure, location tracking
  • ✓Financial Trading: Stock prices, market data, tick-by-tick data
  • ✓Application Performance: Request rates, response times, error rates
Find Your Database