InfluxDB
InfluxDB 2.7 is the platform purpose-built to collect, store, process and visualize time series data. Time series data is a sequence of data points indexed in time order. Data points typically consist of successive measurements made from the same source and are used to track changes over time. Examples of time series data include:
- Industrial sensor data
- Server performance metrics
- Heartbeats per minute
- Electrical activity in the brain
- Rainfall measurements
- Stock prices
Prometheus vs InfluxDB
Data model / storage
Like Prometheus, the InfluxDB data model has key-value pairs as labels, which are called tags. In addition, InfluxDB has a second level of labels called fields, which are more limited in use. InfluxDB supports timestamps with up to nanosecond resolution, and float64, int64, bool, and string data types. Prometheus, by contrast, supports the float64 data type with limited support for strings, and millisecond resolution timestamps.
InfluxDB uses a variant of a log-structured merge tree for storage with a write ahead log, sharded by time. This is much more suitable to event logging than Prometheus’s append-only file per time series approach.
Use Cases
Prometheus was built with monitoring in mind—especially distributed, cloud native monitoring. It excels in this category, featuring lots of useful integrations with other existing products.
While InfluxDB can also handle monitoring, it’s not as popular as Prometheus for accomplishing this task. As a result, you may be required to write your own integrations. However, if you are interested in more than just monitoring, InfluxDB is also a great option for storing time series data, such as data coming from sensor networks or data used in real-time analytics (e.g., financial data or Twitter stats).
Ref
- https://www.metricfire.com/blog/prometheus-vs-influxdb/
- https://medium.com/@squadcast/prometheus-vs-influxdb-choosing-the-right-time-series-database-126d3d17ed3e
- https://grafana.com/blog/2016/01/05/logs-and-metrics-and-graphs-oh-my/
InfluxDB vs ClickHouse
Ref
Reference
- https://en.wikipedia.org/wiki/InfluxDB
- https://docs.influxdata.com/influxdb/v2/get-started/
- https://www.influxdata.com/comparison/clickhouse-vs-influxdb/