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ClickHouse acquires Langfuse

220 points| tin7in | 1 month ago |langfuse.com

96 comments

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rr808|1 month ago

Just did a funding round. In a sign of the times clickhouse used to be an interesting DB product, but is now a "database software that companies can use as they develop AI agents "

<i>Database technology startup ClickHouse Inc. has raised $400 million in a new funding round that values the company at $15 billion — more than double its valuation less than a year ago. </i>

https://www.bloomberg.com/news/articles/2026-01-16/clickhous...

embedding-shape|1 month ago

Investors are finicky creatures, if you've been relying on VC-funding since before, it's hard to stop until you are really successful, and if everyone starts to only look at shiny AI stuff and you still need investors, you end up with not much choice.

I wish there was less of it, we'd have better software then, but :/

debarshri|1 month ago

The fundraising market is very interesting right now. You have to have some AI and agenr narrative without which you do not look very forward looking. You might be a database company with million in revenue but if you do not have a AI narrative you would not be perceived as forward looking as compared to a startup thats burning through millions in token with no path to profitability. It has become table stakes and the new reality for startups.

steveBK123|1 month ago

I think it’s hard to make money as a pure play DB vendor and has been for a decade or two. So they all inevitably pivot into some service specific to whatever the hot use case of the moment is… Cybersecurity. Observability. Crypto. AI.

gyre007|1 month ago

> Our goal continues to be building the best LLM engineering platform

Interesting headline for a checks notes time series database company.

michaelmior|1 month ago

Note that the headline is from Langfuse, not ClickHouse. Reading the announcement from ClickHouse[0], the headline is "ClickHouse welcomes Langfuse: The future of open-source LLM observability". I think the Langfuse team is suggesting that they will be continuing to do the same work within ClickHouse, not that the entire ClickHouse organization has a goal of building the best LLM engineering platform.

[0] https://clickhouse.com/blog/clickhouse-acquires-langfuse-ope...

dangoodmanUT|1 month ago

Your notes aren't very good. They're not a time series database company, they're a columnar database company. But yeah the LLM bit is weird, database companies _always_ feel like charlatans when it comes to LLMs.

cs554|1 month ago

"Berkshire Hathaway Inc. is an American multinational conglomerate holding company" is a weird thing for a textile manufacturer to call itself. Almost like...businesses expand and evolve?

(they've never been a time series database company either lol)

vibedev|1 month ago

But this is correct? The article that you read is from Langfuse POV, not Clickhouse.

wodenokoto|1 month ago

Language models are time series models.

It’s great when you get this insight as a student of NLP, because suddenly your toolset grows quite a bit.

madduci|1 month ago

Diversification is the keyword

mrits|1 month ago

They are closer to an LLM database than a time series database. But they aren't very close to either.

stingraycharles|1 month ago

That’s what you get when you raise a lot of VC capital. Just being the best timeseries database is not enough.

Rafert|1 month ago

I'm surprised it's not mentioned yet, but this seems to compliment last year's acquisition of observability tool HyperDX[1] (part of ClickStack[2]) quite well. I'm in the market for a new o11y platform and it seems all vendors are working to add LLM observability one way or the other, if they haven't added it already.

1: https://news.ycombinator.com/item?id=44194082 2: https://clickhouse.com/use-cases/observability

gandreani|1 month ago

What are you using now and what are you looking for in your new platform?

kankerlijer|1 month ago

For those building applications with Langfuse and Clickhouse - do you like these products? I get the odd request to do an AI thing, and my previous experience with LLM wrappers convinced me to stay away from them (Langchain, Llamaindex, Autogen, others). In some cases they were poorly written, and in other ways the march of progress rendered their tooling irrelevant fairly quickly. Are these better?

deaux|1 month ago

Ive used Langfuse. It's completely unrelated to tools like Langchain and Autogen. It's just logging/tracing for LLMs. Sure they added stuff like "prompt management" and "epxeriments" etc. probably to keep investors happy but those are entirely optional sidedishes.

The tools you mentioned are indeed to be avoided. I trialed them early on and quickly realized in 99.9% they do nothing but bog you down. Pretty sure they'll be dead sooner rather than later.

embedding-shape|1 month ago

The observability stuff can be nice for deployments but really, these libraries/frameworks don't actually do much more than provide some structure, which unless you're expecting a team with high turnover to maintain it, doesn't really matter all that much, especially if you're an experienced developer, you'll find better design/architectures fitting for your use case without them.

agsqwe|1 month ago

We like Langfuse for observability via OpenTelemetry. Prompt management is too basic for our needs.

bezbac|1 month ago

Congratulations to everyone involved, quite remarkable considering Langfuse was only founded as part of YC 23.

shmichael|1 month ago

Without the purchase price, it is unclear whether this deserves congratulations or condolences.

Two years in the LLM race will have definitely depleted their seed raise of $4m from 2023, and with no news of additional funds raised it's more than likely this was a fire sale.

dangoodmanUT|1 month ago

The fact that all metrics are relative doesn't suggest they got an amazing deal

smithclay|1 month ago

This is part of a bigger consolidation trend, AI hype or not: which general-purpose data vendor gets to store and query all of your observability and business data?

Snowflake acquired Observe last week, AWS made it easy in December to put logs from Cloudwatch in their managed iceberg catalog, and Azure is doing a bunch of interesting stuff with Fabric.

The line between your data lake/analytics vendor and observability vendor is getting blurry.

swyx|1 month ago

(congrats team! such a joy to see you succeed)

every single day there is an acquisition on here. what's going on in the macro?

kmlx|1 month ago

maybe clickhouse can finally make sense of the langfuse documentation

7thpower|1 month ago

Langfuse has been my favorite LLM observability solution so far. Hopefully this acquisition makes it better, not worse.

jimmyl02|1 month ago

Clickhouse's full announcement is here https://clickhouse.com/blog/clickhouse-raises-400-million-se... and I think another big piece is directly integrating postgres into their ecosystem.

It seems like an expansion play from their team and their end vision as both a platform (clickhouse + postgres) and product (observability) seems to be pretty good combo that fits hand in hand.

jimmySixDOF|1 month ago

I predict it will be Pydantic next to get picked up by someone for logfire and agent framework.... fine as long as all these open source projects stay open source then good for them

CuriouslyC|1 month ago

The Pydantic stuff is nice, but in a minimalist way that I don't see being amenable to SaaS/vc/etc.

axpy906|1 month ago

SaaS company pivots to AI. Gets funding rebranded as AI company. Buys a company that actually knows it.

It’s still early but I question how much of these SaaS companies will continue. I’d rather connect Claude or whatever to do my task than have to learn a new platform let alone login to it.

antoniojtorres|1 month ago

I don’t think that is a an accurate depiction of ClickHouse. I don’t think they’re pivoting from their main data warehousing product at all. Probably making their cloud offering more competitive with other providers.

amai|1 month ago

What is the advantage of a specialized llm tracing solution like langfuse vs a complete tracing solution like logfire: https://pydantic.dev/logfire ?

amai|1 month ago

Since clickhouse is headquartered in the US that means the langfuse cloud is no longer GDPR compliant.

deaux|1 month ago

Correct! Will be moving away immediately for this reason.

Or well, technically incorrect, as someone will surely point out. US companies can be legally compliant with GDPR, it's just that the likes of the CLOUD Act and FISA make it completely meaningless.

Before anyone comes in talking about how it's farfetched that those matter, it's 100x as far-fetched that self-hosted Chinese LLM models would exfiltrate your data (you can even airgap them) yet 90% of corporate America is avoiding them based solely on the country they were trained in. Compared to that insanity, above US acts are a very real threat.

And that's of course on top of that now an adversarial state's company has the power to immediately dissolve Langfuse.

LunaSea|1 month ago

Isn't ClickHouse owned by Nebius in Amsterdam?

mritchie712|1 month ago

the "Prompt Management" part of these products always seemed odd. Does anyone use it? Why?

dandelionv1bes|1 month ago

I do understand why it’s a product - it feels a bit like what databricks has with model artifacts. Ie having a repo of prompts so you can track performance changes against is good. Especially if say you have users other than engineers touching them (ie product manager wants to AB).

Having said that, I struggled a lot with actually implementing langfuse due to numerous bugs/confusing AI driven documentation. So I’m amazed that it’s being bought to be really frank. I was just on the free version in order to look at it and make a broader recommendation, I wasn’t particularly impressed. Mileage may vary though, perhaps it’s a me issue.

pprotas|1 month ago

Iterating on LLM agents involves testing on production(-like) data. The most accurate way to see whether your agent is performing well is to see it working on production.

You want to see the best results you can get from a prompt, so you use features like prompt management an A/B testing to see what version of your prompt performs better (i.e. is fit to the model you are using) on production.

cunha00|1 month ago

We use it for our internal doc analysis tool. We can easily extract production genrrations, save them to datasets and test edge cases. Also, it allows prompt separation in folders. With this, we have a pipeline for doc abalysis where we have default prompts and the user can set custom prompts for a part of of the pipeline. Execution checks for a user prompt before inference, if not, uses default prompt, which is already cached on code. We plan to evaluate user prompts to see which may perform better and use them to improve default prompt.

mercurialsolo|1 month ago

Clickhouse needs observability models to be more useful to agent run infra

deaux|1 month ago

Very sad, for all their marketing around EU, GDPR, privacy and so on. I feel dumb for having fell for it a little.

This is a big reason why there are so few EU tech startups, they get bought out if they're doing well, more and more consolidation in tech, more and more "exits".

Nora23|1 month ago

Does this mean Langfuse will now have better ClickHouse integration?