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Could you provide more details regarding low quality APIs and PromQL compatibility issues? The following article explains "issues" with PromQL compatibility in VictoriaMetrics - https://medium.com/@romanhavronenko/victoriametrics-promql-c... . See also https://docs.victoriametrics.com/metricsql/ . TL;DR: MetricsQL fixes PromQL issues with rate() and increase() functions. That's why it is "incompatible" with PromQL.

Could you provide examples of FUD marketing from VictoriaMetrics?



I am on mobile, so cannot really link GitHub for examples, but I'd recommend anyone considering using VM over Prometheus to take a cursory look into how similar things are implemented in both projects, and what shortcuts were made in the name of getting "better performance".

Performance-wise e.g. VictoriaMetrics' prometheus-benchmark only covered instant queries without look back for example the last time I checked.

Regarding FUD marketing: All Prometheus community channels (mailing lists, StackOverflow, Reddit, GitHub, etc.) are full of VM devs pushing VM, bashing everything from the ecosystem without mentioning any of the tradeoffs. I am also not aware of VictoriaMetrics giving back anything to the Prometheus ecosystem (can you maybe link some examples if I am wrong?) which is a very similar to Microsoft's embrace, extend, and extinguish strategy. As per recent actual examples, here's a 2 submission of the same post bashing project in the ecosystem: https://news.ycombinator.com/item?id=40838531, https://news.ycombinator.com/item?id=39391208, but it's really hard to avoid all the rest in the places mentioned above.


> Performance-wise e.g. VictoriaMetrics' prometheus-benchmark only covered instant queries without look back for example the last time I checked.

prometheus-benchmark ( https://github.com/VictoriaMetrics/prometheus-benchmark ) tests CPU usage, RAM usage and disk usage for typical alerting queries. It doesn't test the performance of queries used for building graphs in Grafana because the typical rate of alerting queries is multiple orders of magnitude bigger than the typical rate of queries for building graphs, e.g. alerting queries generate the most of load on CPU, RAM and disk IO in typical production workload.

Please file a feature request at https://github.com/VictoriaMetrics/prometheus-benchmark/issu... to add the ability to test resource usage for typical queries for building Grafana graphs if you think this will be a good feature.

> I am also not aware of VictoriaMetrics giving back anything to the Prometheus ecosystem (can you maybe link some examples if I am wrong?)

Sure:

- https://github.com/prometheus/prometheus/issues?q=author%3Av...

- https://github.com/prometheus/prometheus/issues?q=author%3Al...

- https://github.com/prometheus/prometheus/issues?q=author%3Ah...

> As per recent actual examples, here's a 2 submission of the same post bashing project in the ecosystem: https://news.ycombinator.com/item?id=40838531

This submission posts a link to the real-world experience of long-term user of Grafana Loki. This user points to various issues in applications he uses. For example:

- Issues with Loki restarts - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

- Issues with structured metadata in Loki 3.0 - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

- Issues with single-node Loki setup - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

- Issues with Loki logcli command - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

- Issues with Grafana Loki data compaction - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

- Comparison of Grafana Loki vs traditional syslog server - https://utcc.utoronto.ca/~cks/space/blog/sysadmin/GrafanaLok...

As you can see, this user shares his extensive experience with Grafana Loki, and continues using it despite the fact that there is much better solution exists, which is free from all the Loki issues - VictoriaLogs. This user isn't affiliated with VictoriaMetrics in any way.




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