Maybe because some open-source software has limitations? That seems reasonable to me.
51 karma · joined January 9, 2020
Maybe because some open-source software has limitations? That seems reasonable to me.
Vertically on a single machine, the two are quite similar, both fan work out across all CPU cores. The different is on scaling out.
ClickHouse scales by making you describe the cluster yourself. You decide how many shards to split the data into, how many copies (replicas) each shard keeps, which row goes to which shard. The copies are kept in sync by a consensus system ClickHouse Keeper. This is flexible but also more works on operators.
VictoriaLogs takes the opposite bet. When logs come in, the inserter just spreads them across all storage nodes on its own, so there is no sharding key for you to design. When a query runs, the selector asks every storage node in parallel and merges the results. There is no consensus system at all. If you want high availability, you run 2 independent clusters and send your logs to both, rather than having the database copy data internally. So this is simpler and less learning curve. See more here https://victoriametrics.com/blog/victorialogs-architecture-b...
ClickStack also looks promising.
Maybe it is fast because it is not secured at all? :D
Where was this mentioned?
Does anyone know what's going on?
The Problem with Prometheus At scale, Prometheus started showing limitations, especially for large enterprise customers like Pinterest.The main issues were: - High resource consumption: Prometheus used a lot of CPU and memory, leading to frequent out-of-memory (OOM) crashes. - Long recovery times: After a crash, Prometheus needed a long time to recover, sometimes failing altogether. - Limited query performance: Large queries would often fail or be very slow.
The Solution: VictoriaMetrics
TiDB switched to VictoriaMetrics and saw significant improvements: - Better resource utilization: CPU and memory usage dropped significantly, eliminating OOM crashes. - Improved query performance: Large queries that previously failed in Prometheus now run efficiently in VictoriaMetrics. - Lower costs: Reduced resource consumption and better storage efficiency led to lower operational costs.
Have you had a chance to play with VictoriaLogs? If not, then I highly recommend to test it. Our team is also working on implementing traces in top of Jaeger and VictoriaLogs, see https://victoriametrics.com/blog/dev-note-distributed-tracin...
My question is: is it really convenient to use only SaaS now if there is always the possibility of losing your data? I am referring to the case described in the article.
[1]: https://vrutkovs.eu/posts/home-infra/ [2]: https://github.com/VictoriaMetrics-Community/homeassistant-a...
PS: I'm working at VictoriaMetrics company