[HN Gopher] ClickHouse acquires Langfuse
___________________________________________________________________
ClickHouse acquires Langfuse
Author : tin7in
Score : 190 points
Date : 2026-01-17 09:15 UTC (13 hours ago)
(HTM) web link (langfuse.com)
(TXT) w3m dump (langfuse.com)
| kmlx wrote:
| maybe clickhouse can finally make sense of the langfuse
| documentation
| tuananh wrote:
| how does it benefit for clickhouse?
| ushakov wrote:
| they want to enter the llm observability market and langfuse
| has already built a convenient wrapper around clickhouse that
| companies have adopted
|
| https://clickhouse.com/blog/clickhouse-raises-400-million-se...
| tuananh wrote:
| thank you! i missed that news
| mercurialsolo wrote:
| Clickhouse needs observability models to be more useful to agent
| run infra
| ponywombat wrote:
| Ah, the painful migration to Clickhouse from v2 to v3 makes sense
| now https://langfuse.com/self-hosting/upgrade/upgrade-
| guides/upg...
| __s wrote:
| This is not why v3 made those changes over a year ago, your
| cause & effect are mistaken
| bezbac wrote:
| Congratulations to everyone involved, quite remarkable
| considering Langfuse was only founded as part of YC 23.
| shmichael wrote:
| 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.
| stuartjohnson12 wrote:
| Anecdotally, from the AI startup scene in London, I do not
| know folks who swear by Langfuse. Honestly, evals platforms
| are still only just starting to catch on. I haven't used any
| tracing/monitoring tools for LLMs that made me feel like,
| say, Honeycomb does.
| 7thpower wrote:
| I love langfuse, it is my goto.
| topicseed wrote:
| I'd say out of many generative AI observability platforms,
| Langsmith and Weave (Weights&Biases) are probably the ones
| most enterprises use, but there's definitely space for
| Langfuse, Modelmetry, Arize AI, and other players.
| jascha_eng wrote:
| It was not a fire sale I'm pretty sure. Langfuse has been
| consistently growing, they publish some stats about sdk usage
| etc so you can look that up.
|
| They also say in the announcement that they had a term sheet
| for a good series a.
|
| I think the team just took the chance to exit early before
| the llm hype crashes down. There is also a question of how
| big this market really is they mostly do observability for
| chatbots but there are only so many of those and with other
| players like openais tracing, pydantic logfire, posthog etc
| they become more a feature than a product of its own. Without
| a great distribution system they would eventually fall behind
| I think.
|
| 2 years to a decent exit (probably 100m cash out or so with a
| good chunk being Clickhouse shares) seems like a good idea
| rather than betting on that story to continue forever.
| axpy906 wrote:
| I don't know about that. I looked at them a couple of
| months back for prompt management and they were pretty
| behind in terms of features. Went with PromptLayer
| floriferous wrote:
| Agreed, Sentry, Posthog, and many more are all doing the
| exact same thing now, I'd be surprised if this was a good
| deal for Langfuse. I personally migrated away from it to use
| Sentry, their software was honestly not that great.
| dangoodmanUT wrote:
| The fact that all metrics are relative doesn't suggest they got
| an amazing deal
| mritchie712 wrote:
| the "Prompt Management" part of these products always seemed odd.
| Does anyone use it? Why?
| dandelionv1bes wrote:
| 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.
| alexpadula wrote:
| I thought the docs were pretty good just going through them
| to see what the product was. For me I just don't see the use-
| case but I'm not well versed in their industry.
| dandelionv1bes wrote:
| I think the docs are great to read, but implementing was a
| completely different story for me, ie, the Ask AI
| recommended solution for implementing Claude just didn't
| work for me.
|
| They do have GitHub discussions where you can raise things,
| but I also encountered some issues with installation that
| just made me want to roll the dice on another provider.
|
| They do have a new release coming in a few weeks so I'll
| try it again then for sure.
|
| Edit: I think I'm coming across as negative and do want to
| recommend that it is worth trying out langfuse for sure if
| you're looking at observability!
| pprotas wrote:
| 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 wrote:
| 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.
| swyx wrote:
| (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?
| marcklingen wrote:
| (thank you!)
| Nora23 wrote:
| Does this mean Langfuse will now have better ClickHouse
| integration?
| jimmySixDOF wrote:
| 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 wrote:
| The Pydantic stuff is nice, but in a minimalist way that I
| don't see being amenable to SaaS/vc/etc.
| scolvin wrote:
| We have a SaaS platform (Pydantic Logfire - General and AI
| observability), and we raised our Series A from Sequoia.
|
| For good or bad, I think we're pretty "SaaS/vc/etc." already.
| saberience wrote:
| Yeah it seems a bit forced though. Like why go from an open
| source utility library for typing to take VC money and try
| to shoe-horn in an observability platform that no one was
| asking for?
|
| My prediction, not going to be a good investment.
| gyre007 wrote:
| > Our goal continues to be building the best LLM engineering
| platform
|
| Interesting headline for a _checks notes_ time series database
| company.
| stingraycharles wrote:
| That's what you get when you raise a lot of VC capital. Just
| being the best timeseries database is not enough.
| michaelmior wrote:
| 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...
| cs554 wrote:
| "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)
| wodenokoto wrote:
| 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.
| Jgrubb wrote:
| Could you elaborate? because that sentence made my brow
| wrinkle with confusion. I have thought to myself before that
| all business data problems eventually become time series
| problems. I'd like to understand your point of view on how
| LLMs fit into that.
| wodenokoto wrote:
| Time series just means that the order of features matter.
| Feature 1 occurs before feature 2.
|
| E.g, fitting a model to house prices, you don't care if
| feature 1 is square meters and feature 2 is time on market,
| or vice versa, but in a time series, your model changes if
| you reverse the order of features.
|
| With text, the meaning of word 2 is dependent on the
| meaning of word 1. With stock prices, you expect the price
| at time 2 to be dependent on time 1.
|
| Text can be modeled as a time series.
|
| A language model tells you the next character/token/word
| depending on the previous input.
|
| Language models are time series.
|
| It's not an audacious claim.
|
| Any student of nlp should have met a paper modeling text as
| time series before writing their thesis. How could you not
| meet that?
| thesz wrote:
| [1] https://towardsdatascience.com/llm-powered-time-series-
| analy...
|
| [2] https://arxiv.org/abs/2506.02389
|
| [3] https://arxiv.org/html/2402.10835v3
|
| Some links from the top of Google search.
|
| Take a look here, also, it's an important law:
| https://en.wikipedia.org/wiki/Benford%27s_law
|
| It is possible for LLMs to learn Bernford's law,
| implicitly. So they will be non-null predictors of time
| series data, because time series data is also Bernford-law-
| distributed [4].
|
| [4] https://ui.adsabs.harvard.edu/abs/2017EGUGA..19.2950T/a
| bstra...
| dangoodmanUT wrote:
| 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.
| vegabook wrote:
| Willing to bet most columnar stores are used for time series.
| domoritz wrote:
| I suspect most use of columnar databases is OLAP, which is
| different from what people usually mean when they say time
| series data.
| goodkiwi wrote:
| I'd take that bet
| vibedev wrote:
| But this is correct? The article that you read is from Langfuse
| POV, not Clickhouse.
| mrits wrote:
| They are closer to an LLM database than a time series database.
| But they aren't very close to either.
| madduci wrote:
| Diversification is the keyword
| rr808 wrote:
| 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 wrote:
| 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 :/
| esafak wrote:
| Would we? You can look at places with less funding and see
| how many software companies get off the ground.
| embedding-shape wrote:
| > You can look at places with less funding
|
| Yeah, like FOSS which is drastically underfunded since
| birth, yet continues to put out software that the entire
| world ends up relying on, instead of relying on whatever
| VC-pumped companies are putting out.
|
| I'm not talking "better software" as in "made a lot of
| money", I meant "better" as in "had a better impact on the
| world".
| esafak wrote:
| FOSS software is written by people working at companies
| that likely owe their existence to VC.
| hrimfaxi wrote:
| What gave you that idea?
| esafak wrote:
| Because Silicon Valley, which contributes the majority of
| the code, is venture backed. For example, 84% of the
| Linux kernel's development is corporate:
| https://commandlinux.com/statistics/linux-foundation-
| growth-...
|
| I don't know why people are so upset here.
| weiliddat wrote:
| That sounds like more sign of recent times.
|
| FOSS software that many rely on that has been around for
| a while were non-VC: VCS, Linux / GNU / BSD, web
| browsers, various programming languages, various
| databases...
| rhplus wrote:
| Sure, those projects were un(der)funded in the 80s and
| 90s but the reason we talk about them today is because of
| the huge amount of investment - both direct and in kind -
| that VC backed companies have managed to give to many of
| them.
|
| I think it's easy to forget how long ago it was when FOSS
| truly was the outsider and wouldn't be touched by most
| companies.
|
| Mozilla/Firefox started in 1998 and then started taking
| ad revenue from Google in 2005, which pays for a large
| chunk of its development. It's been part of the Silicon
| Valley money machine for 20 years, most of its existence.
| jedberg wrote:
| Many of your examples came from people who were funded by
| Universities in the 80s, which was basically the VC of
| the time. And in the 90s, a lot of the core committers of
| those projects were already working at VC funded
| companies.
|
| Back then it was very normal to get VC funding and then
| hire the core committers of your most important open
| source software and pay them to keep working on it. I
| worked at Sendmail in the 90s and we had Sendmail
| committers (obviously) but also BSD core devs and linux
| core devs on staff. We also had IETF members on staff.
|
| And we weren't unique, this happened a lot.
| weiliddat wrote:
| Thanks for the insight and history. Glad to be corrected.
|
| Was it in a different nature to current VC funded FOSS
| though? It sounds like their contributions to FOSS was
| tangential and not the sold product?
|
| Maybe a bit more like Google and Chrome?
| TheTaytay wrote:
| I don't know why you are being downvoted. I mean, I guess
| I do, but sheesh, they are really shooting the messenger
| here. Maybe they are looking for more nuance: a lot of
| software is/was written by people working at...
|
| I don't think everything VCs touch is gold, but it's also
| not the case that they are pure evil either. It's almost
| as if you can't claim they are all good or all bad.
| CodingJeebus wrote:
| I sometimes wonder if the VC ecosystem creates its own
| confirmation bias by making it easy to see and aggregate
| companies it incubates. Whenever I look for jobs, I'm
| always surprised to find companies that have taken no VC
| funding and don't try particularly hard to market to the
| industry as a whole, preferring instead to stay relatively
| under the radar.
|
| They tend to have more grounded financials (read: paths to
| profitability) and while the pay packages aren't quite
| aligned with the top end of the market, they also tend to
| manage headcount more responsibly than FAANG. I work with a
| fairly niche stack and I'm constantly finding new companies
| that I've never heard of and don't raise VC rounds.
|
| Long way of saying that just because they're not easy to
| find doesn't mean they don't exist.
| shimman wrote:
| What but? If this is the "best" that VC can do with the
| money, the US government should simply tax it away from them.
| Absolutely worse way to allocate resources and develop a
| robust forward looking tech industry, you're just chasing the
| shiny while fucking over the commons.
| embedding-shape wrote:
| Maybe my point wasn't clear, I agree with you. It's a bad
| way of allocating resources, and we'd had better software
| had we been without it.
| steveBK123 wrote:
| 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.
| debarshri wrote:
| 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.
| data-ottawa wrote:
| This has made buying products hard.
|
| What do you do? "We power your agents" okay... but what do
| you do? How do you do that?
|
| Every DB, storage system, and analytics tool website is like
| this lately.
| nikcub wrote:
| Clickhouse are on a bit of a roll. acquired peerdb and are
| doing a hosted postgres product[0]
|
| Acquired hyperdx[1] for their clickstack[2] observability
| platform and adding langfuse to a bunch of other llm related
| acquisitions and products
|
| They're really building out a snowflake / databricks
| alternative
|
| [0] https://clickhouse.com/cloud/postgres
|
| [1] https://clickhouse.com/docs/cloud/manage/hyperdx
|
| [2] https://clickhouse.com/use-cases/observability
| 7thpower wrote:
| Langfuse has been my favorite LLM observability solution so far.
| Hopefully this acquisition makes it better, not worse.
| CuriouslyC wrote:
| As a big Clickhouse fan, agent evals are where their product
| really shines. They're buying into market segment where their
| product is succeeding so they can vertically integrate and
| tighten up the feedback loop.
| dpkirchner wrote:
| Are you talking about this sort of thing?
| https://clickhouse.com/blog/tracing-openai-agents-clickstack
| kankerlijer wrote:
| 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?
| embedding-shape wrote:
| 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.
| st3fan wrote:
| Hm I find this very much a "please reinvent the wheel" take.
|
| These frameworks provide structure for established
| patterns,but they also actually do a lot that you don't have
| to do anymore. If you are for example building an agentic
| application then these kind of frameworks make it very simple
| to create the workflows, do the chat with the model
| providers, provide structure for agentic skills, decision
| making and the human in the loop, etc. etc.
|
| All stuff that I would consider "low level". All things you
| don't have to build.
|
| If you have an aversion to frameworks then sure - by all
| means. But if you like to move faster and using good building
| blocks then these frameworks really help.
|
| One thing to keep in mind - many of these AI frameworks are
| open source and work really well without needing backend
| services. Or you can self host them where needed. But for
| many that is also the premium model, please use and pay for
| our backend services. But that is also a choice of course.
| embedding-shape wrote:
| > All stuff that I would consider "low level". All things
| you don't have to build.
|
| But those are also very trivial to build, and you end up
| having to customize them for your need, and if the
| framework don't have those levers, better be prepared to
| either fork the framework, or spend time contributing
| upstream.
|
| Or, start simple yourself with what you need, use libraries
| for the hairy parts you don't want to be responsible for
| the implementation of, then pipe these things together.
| You'll get a less compromised experience, and you'll
| understand 100% how everything works, which is the part
| people generally try to avoid and that's why they're
| reaching for frameworks.
|
| > But if you like to move faster and using good building
| blocks then these frameworks really help.
|
| I find that they help a lot with the "move faster" part in
| the beginning, but after that period, they slow you down
| instead. But I'm also a person that favors "slow software
| design and development" where you take your time to nail
| down a good design/architecture before you run. Slow is
| fast, and avoiding hairballs is the most important part if
| you're aiming for "move fast for longer" rather than "a
| sprint of fast".
| deaux wrote:
| 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.
| amai wrote:
| What is the advantage of a specialized llm tracing solution like
| langfuse vs a complete tracing solution like logfire:
| https://pydantic.dev/logfire ?
| axpy906 wrote:
| 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 wrote:
| 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.
| axpy906 wrote:
| I haven't used their product so you're probably right. I'm
| biased as an AI engineer because I get contacted to help
| implement AI in existing platforms. While I admire the pivot
| the reality is what they have is already quite behind.
| Anything I make these days is old in about three months...
| You'd ideally want to start fresh and not have to worry about
| codebase that is years old.
| amai wrote:
| Since clickhouse is headquartered in the US that means the
| langfuse cloud is no longer GDPR compliant.
| deaux wrote:
| 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.
| Rafert wrote:
| 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 wrote:
| What are you using now and what are you looking for in your new
| platform?
| smithclay wrote:
| 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.
| deaux wrote:
| 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".
| jimmyl02 wrote:
| 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.
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