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dengolius

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The answer to your question was deleted, so I'll post it again:

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...

I read somewhere that the owners have ties to russia, but the most important thing is that they’re marketing very aggressively through posts that slander GraphenOS.

[dead] 12 months ago

502 Bad Gateway

Does anyone know what's going on?

This article discusses why TiDB, a distributed SQL database, migrated its observability platform from Prometheus to VictoriaMetrics.

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.

My friend uses self-hosted open-source software to monitor all his home IoT devices[1] and copies important information to the cloud. I'm using StarFive VisionFive 2 to host my database for monitoring, but also have a copy of the data of a chip hetzner arm vps, as well as hosting backups on the two different clouds. I know users who are running[2] for years to monitor Solar panels, lawn watering and vegetable garden watering.

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