Time-Series Database
A database optimized for time-stamped data points like metrics, sensor readings, and financial ticks. InfluxDB and TimescaleDB are purpose-built for this.
What is Time-Series Database?
A database optimized for time-stamped data points like metrics, sensor readings, and financial ticks. InfluxDB and TimescaleDB are purpose-built for this.
Time-Series Database is a intermediate-level concept that sits in the Database Types & Storage area of system design. Engineers reach for it whenever they need to reason about real-world trade-offs in that space — not just for textbook correctness, but because real production systems at companies like Netflix, Amazon, and Google make these decisions every day.
If you want to go deeper than this definition — with diagrams, code, and a quiz to lock it in — work through the "Time-Series Database" lesson linked below. It walks through the why, the mechanism, the trade-offs, and how the giants actually use it in production.
Learn Time-Series Database in depth
Full interactive lesson with diagrams, code examples, real-world references, and a quiz.
Open the Time-Series Database lessonRelated lessons
Lessons that touch on Time-Series Database as part of a larger topic.
Time-Series Databases
Databases built for timestamped data, metrics, IoT sensors, financial ticks, and observability
intermediate · database types storage
Design a Metrics/Monitoring System
Design a metrics collection and monitoring system - time-series databases, aggregation pipelines, alerting, and dashboards at scale
capstone · capstone
See also
Related glossary terms you might want to look up next.
NoSQL
Databases that don't use traditional table-based relational models. Includes document stores, key-value, graph, and column-family databases.
Stream Processing
Processing data continuously as it arrives, rather than in batches. Powers real-time analytics, fraud detection, and live dashboards.
Observability
The ability to understand a system's internal state from its external outputs. Built on three pillars: metrics, logs, and traces.