What is Time-Series Database?
Turkish: Zaman Serisi Veritabanı
A time-series database optimizes storage, compression, and time-based queries for timestamped metrics, logs, and sensor data.
What is a Time-Series Database?
A time-series database is designed for data where each record is meaningful because of its timestamp. Server CPU usage, IoT sensor temperature, application response time, and stock prices all ask the same basic question: what value was observed at what time?
How Does It Work?
Time-series systems prioritize high write volume, time-based partitioning, and fast range queries. Records usually contain a measurement name, timestamp, tags, and field values. Tags identify dimensions such as device, region, or service; fields store the measured values.
Common capabilities include:
- Retention: Automatically deleting or archiving old data
- Downsampling: Turning minute-level data into hourly or daily summaries
- Compression: Storing similar values from nearby time ranges efficiently
- Rollup queries: Quickly retrieving averages, maximums, or 95th percentiles
Business Use
Time-series databases are used in monitoring, energy tracking, manufacturing line measurements, fleet telemetry, and IoT platforms. Prometheus, InfluxDB, and TimescaleDB are common examples. Without retention and aggregation policies, data volume can quickly become a cost problem.