Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
blog.timescale.com
Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
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Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#2https://github.com/ClickHouse/ClickHouse/graphs/contributors
https://github.com/elastic/elasticsearch/graphs/contributors
Edit: I was very off. The Github contributor graph does not show all actual contributors. ElasticSearch has somewhere around 2-3 times as many contributors as ClickHouse.
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#3I was surprised to see that ClickHouse and ElasticSearch have the same number of contributors. That's pretty astounding given how much older and more prominent ElasticSearch has been. https://github.com/ClickHouse/ClickHouse/graphs/contributors https://github.com/elastic/elasticsearch/graphs/contributors Edit: I was very off. The Github contributor graph does not show all actual contributors. ElasticSearch has somewh…
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#4Simple avg, etc were better, but always clickhouse was an order of magnitude faster than timescale. We didn't invest a whole bunch into optimization other than trying some indexing strategies in timescaledb.
So for our use case the choice is clear.
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#5Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#6Has anyone else been seeing an influx of timescale.com articles? I count around 10 in the last month.
We've been working really hard on our launches / releases this month! We called it "Always Be Launching" - we've been aiming for releasing multiple things per week during October :)
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#7Our anecdata: we store telemetry per thing. After loading a month worth of data - timescaldb as hosted by their cloud ran a difference aggregation in seconds. Clickhouse routinely did it in 20 millis. Simple avg, etc were better, but always clickhouse was an order of magnitude faster than timescale. We didn't invest a whole bunch into optimization other than trying some indexing strategies in timescaledb. So for our…
Thanks for the feedback. Without knowing your situation, one of the things we show in the blog post is that TimescaleDB compression often changes the game on those kinds of queries (data is transformed to columnar storage when you compress). You don't mention if you did that or not, but it's something we've seen/noticed in every other benchmark at this point - that folks don't enable it for the benchmark.
And second point of the article is that you have lots of options for whatever works in your specific situation. But, make sure you're using the chosen database features before counting it out. :-)
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#8From what I see, the trade off in disk space usage would point me toward Timescale for most of my workloads. The insert performance tradeoff just wouldn’t justify the difference for me.
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#9Everyone involved should face the firing squad.
Re: Comparing ClickHouse to PostgreSQL and TimescaleDB for time-series data
#10I was surprised to see that ClickHouse and ElasticSearch have the same number of contributors. That's pretty astounding given how much older and more prominent ElasticSearch has been. https://github.com/ClickHouse/ClickHouse/graphs/contributors https://github.com/elastic/elasticsearch/graphs/contributors Edit: I was very off. The Github contributor graph does not show all actual contributors. ElasticSearch has somewh…