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README.md: add a chapter about downsampling

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Aliaksandr Valialkin 2019-06-12 01:32:26 +03:00
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@ -74,6 +74,7 @@ Cluster version is available [here](https://github.com/VictoriaMetrics/VictoriaM
- [Capacity planning](#capacity-planning)
- [High availability](#high-availability)
- [Multiple retentions](#multiple-retentions)
- [Downsampling](#downsampling)
- [Scalability and cluster version](#scalability-and-cluster-version)
- [Security](#security)
- [Tuning](#tuning)
@ -431,6 +432,18 @@ Just start multiple VictoriaMetrics instances with distinct values for the follo
* `-httpListenAddr`, so clients may reach VictoriaMetrics instance with proper retention
### Downsampling
There is no downsampling support at the moment, but:
- VictoriaMetrics is optimized for querying big amounts of raw data. See benchmark results for heavy queries
in [this article](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae).
- VictoriaMetrics has good compression for on-disk data. See [this article](https://medium.com/@valyala/victoriametrics-achieving-better-compression-for-time-series-data-than-gorilla-317bc1f95932)
for details.
These properties reduce the need in downsampling. We plan implementing downsampling in the future.
See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/36) for details.
### Scalability and cluster version
Though single-node VictoriaMetrics cannot scale to multiple nodes, it is optimized for resource usage - storage size / bandwidth / IOPS, RAM, CPU.