Looks very nice, I look forward to checking it out.

I'm curious: why do you maintain separate trees for the single node vs.
cluster version? Naively I would have assumed that single node == cluster
codebase with a few features turned off at runtime, and there seems to be a
lot of overlap between the branches. So I'm wondering what the history is :)

- Dave

On Tue, Jun 18, 2019 at 6:15 AM Aliaksandr Valialkin <valy...@gmail.com>
wrote:

> Hello all,
>
> I'm happy to announce VictoriaMetrics - fast open source time series
> database written in Go -
> https://github.com/VictoriaMetrics/VictoriaMetrics .
> It is written entirely in Go except of gozstd
> <https://github.com/valyala/gozstd> part, which is a cgo wrapper for zstd
> <http://facebook.github.io/zstd/>. It has the following features:
>
> - It contains simple Go code without complex abstractions and fancy
> algorithms, so everyone can inspect it and contribute to it
> <https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/README.md#community-and-contributions>
> .
> - It contains the minimum number of external dependencies - see go.mod
> <https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/go.mod>.
> This means faster compile times and slimmer binaries. Read more about
> stripping dependency bloat here
> <https://medium.com/@valyala/stripping-dependency-bloat-in-victoriametrics-docker-image-983fb5912b0d>
> .
> - It doesn't use mmap and WAL. Read more about this in the following
> articles:
>    *
> https://medium.com/@valyala/mmap-in-go-considered-harmful-d92a25cb161d
>    *
> https://medium.com/@valyala/wal-usage-looks-broken-in-modern-time-series-databases-b62a627ab704
> - It is easy to configure and operate.
> - It is designed to be used as long-term storage for Prometheus.
> - It may collect data from multiple Prometheus instances via standard
> remote write API
> <https://prometheus.io/docs/operating/integrations/#remote-endpoints-and-storage>,
> so the data may be queried later in a single query (aka global querying
> view).
> - It provides PromQL
> <https://medium.com/@valyala/promql-tutorial-for-beginners-9ab455142085>-compatible
> query language, so it may be used as drop-in replacement for Prometheus
> dashboards in Grafana.
> - It is optimized for speed and low resource usage.
> - It provides good on-disk compression
> <https://medium.com/@valyala/victoriametrics-achieving-better-compression-for-time-series-data-than-gorilla-317bc1f95932>
> that is better than Gorilla compression
> <https://blog.acolyer.org/2016/05/03/gorilla-a-fast-scalable-in-memory-time-series-database/>.
> This means more data may be stored without downsampling.
> - It provides free open source cluster version
> <https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster>.
>
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