31–40 of 76 posts
I remember reading that Clickhouse is quite bad at joins, which can be important if you have to build a snowflake schema. Is that still true? Is this something TimescaleDB would be better at?
There is Clickhouse FDW for PostgreSQL which in some cases can provide great speed with full join support
Earlier quoted context omitted.
Honestly, you sound like the bully here hiding behind the overly positive language of the day in order to insult the character of your opponent.
OP made accusations, response was leveled and asked for positivity.
Here, I provided a link to the previous discussion, because personally, I do not appreciate being mislead. I encourage you to check the technical details there if you don't believe me.
But maybe not being 100% positive and supportive is no longer acceptable in 2021? Or maybe it's the complexity of the issues discussed?
So let's give a simpler message: as rkwasni said it best just yesterday: "It's really quite easy, if you don't need DELETE ClickHouse wins every benchmark" https://news.ycombinator.com/threads?id=rkwasny
It's simple as that: if you need deletion, consider TimescaleDB.
For every other conceivable scenario, ClickHouse is likely to come ahead, unless you are doing something very very wrong with it: a virtualization example would be splitting cores across VM with no respect of their shared cache.
When people talk about doing a millions of tiny inserts, it's a bit like that: a misconfiguration. And that's not how it work in the real world: even with plain Postgres, you often use a middle layer to avoid resource issues (increasing max_connections has a cost, that's why pgpool exist!), either directly in your app, or by putting some kind of buffer in front of the real table.
ClickHouse has such features, to automatically handle the flushing to the real table: https://clickhouse.com/docs/en/engines/table-engines/special...
I have spend some serious time with both, think of me what you may, but the CEO of TimescaleDB saying TimescaleDB performance can withstand the comparison with ClickHouse is like Intel marketing department saying Intel CPUs can withstand the comparison with AMD: unless you cook the tests with some highly specific workloads (say with lots of simd/AVX512 stuff, monocore...) to be non representative of the most common scenarios, you're not being honest.
I believe such thinly veiled dishonesty is a much larger problem than a perceived positivity.
Wait was not TimescaleDB completely leave Clickhouse in the dust both in terms of query performance and compression ? https://blog.timescale.com/blog/what-is-clickhouse-how-does-... I think this series of posts confirms the first law of Benchmarketing - for any system one can come up with "unbiased" benchmark which confirms its superiority
I remember reading that Clickhouse is quite bad at joins, which can be important if you have to build a snowflake schema. Is that still true? Is this something TimescaleDB would be better at?
In this case PostgreSQL may be able to come to the rescue :) There is Clickhouse FDW for PostgreSQL which in some cases can provide great speed with full join support https://github.com/adjust/clickhouse_fdw
(Timescale co-founder) I'll answer this here with a similar response that I gave Pradeep (the author) via Twitter. I think ClickHouse is a great technology. It totally beats TimescaleDB for OLAP queries. I'll be the first to admit that. What our (100+ hour, 3 month analysis) benchmark showed is that for _time-series workloads_, TimescaleDB fared better. [0] Pradeep's analysis - while earnest - is essentially comparin…
Even looking at your benchmark queries, I'm confused what value it provides over a standard OLTP or OLAP setup.
(Timescale co-founder) I'll answer this here with a similar response that I gave Pradeep (the author) via Twitter. I think ClickHouse is a great technology. It totally beats TimescaleDB for OLAP queries. I'll be the first to admit that. What our (100+ hour, 3 month analysis) benchmark showed is that for _time-series workloads_, TimescaleDB fared better. [0] Pradeep's analysis - while earnest - is essentially comparin…
I honestly don't know what time-series databases do that's particularly unique. I've worked databases for 20+ years and a date or datetime has always been an integral part of the dataset and thus everything to me is time-series. I always seem them compared against key-value stores or document-oriented databases or NoSQL platforms, which more speaks to people not knowing how to use the correct datastore in the first p…
Earlier quoted context omitted.
OP made accusations, response was leveled and asked for positivity.
Sometimes, after trying to engage positively and giving the benefit of doubt, I start to notice some disturbing things. When that happens, I speak my mind, and escalate progressively depending on how trustworthy I believe the person I'm talking to is. Here, I provided a link to the previous discussion, because personally, I do not appreciate being mislead. I encourage you to check the technical details there if you d…
(Timescale co-founder) I'll answer this here with a similar response that I gave Pradeep (the author) via Twitter. I think ClickHouse is a great technology. It totally beats TimescaleDB for OLAP queries. I'll be the first to admit that. What our (100+ hour, 3 month analysis) benchmark showed is that for _time-series workloads_, TimescaleDB fared better. [0] Pradeep's analysis - while earnest - is essentially comparin…
I honestly don't know what time-series databases do that's particularly unique. I've worked databases for 20+ years and a date or datetime has always been an integral part of the dataset and thus everything to me is time-series. I always seem them compared against key-value stores or document-oriented databases or NoSQL platforms, which more speaks to people not knowing how to use the correct datastore in the first p…
Often there are other time-related stuff in there as well, but I think the vast majority of use is fast calculation of "mean/max/first value of sensor(s) for X-second buckets".
Earlier quoted context omitted.
OP made accusations, response was leveled and asked for positivity.
Sometimes, after trying to engage positively and giving the benefit of doubt, I start to notice some disturbing things. When that happens, I speak my mind, and escalate progressively depending on how trustworthy I believe the person I'm talking to is. Here, I provided a link to the previous discussion, because personally, I do not appreciate being mislead. I encourage you to check the technical details there if you d…