Time-Series Databases
A time-series database stores measurements together with the time each measurement occurred. It helps you ingest, retain, and query changing values such as system metrics, sensor readings, prices, and events over time.
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Intro
Time-Series Databases
A time-series database, often called a TSDB, is built for data that changes over time. Each observation has a timestamp and one or more values. A CPU sample, a temperature reading, and a request counter are all examples.
Time is not just another column in this workload. You usually write new observations continuously, ask for a bounded interval, group observations into time windows, and keep recent detail longer than old detail. A TSDB organizes storage and query paths around those habits.
What you store
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Sources
- https://docs.influxdata.com/influxdb3/core/get-started/
Supports
- InfluxDB 3 databases, tables, tags, fields, time, and primary keys
- Tags as identifying information and fields as measured data
- https://docs.influxdata.com/influxdb3/core/write-data/best-practices/schema-design/
Supports
- Time-series schema design, tags versus fields, timestamps, and query-oriented tag order
- Wide schemas and tag-related performance considerations
- https://docs.influxdata.com/influxdb3/core/reference/line-protocol/
Supports
- A point as table, tag set, field set, and timestamp
- Observation time versus host receipt time
- https://docs.timescale.com/use-timescale/latest/hypertables/
Supports
- Hypertables as PostgreSQL tables automatically partitioned by time
- Chunks and time-based query targeting
- Quiz answer about hypertables
- https://prometheus.io/docs/concepts/
Supports
- Time series as timestamped values identified by metric name and labels
- Samples, metric names, labels, and dimensional data model
- Quiz answers about series identity and query shape
- https://prometheus.io/docs/prometheus/2.55/querying/basics/
Supports
- Instant queries, range queries, and range vectors
- https://prometheus.io/docs/prometheus/3.5/storage/
Supports
- Local TSDB blocks, chunks, indexes, and write-ahead logging
- https://github.com/lmmentel/awesome-time-series
Supports
- ClickHouse, CrateDB, and Apache Druid as ecosystem resources