5 ms·

> Our goal continues to be building the best LLM engineering platform Interesting headline for a checks notes time series database company.

by gyre007 9mo ago

stingraycharles 9mo ago
That’s what you get when you raise a lot of VC capital. Just being the best timeseries database is not enough.
nsmdkdfk 9mo ago
[dead]
michaelmior 9mo 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-open-source-llm-observability https://clickhouse.com/blog/clickhouse-acquires-langfuse-ope...
cs554 9mo 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)
wodenokoto 9mo 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.
- Jgrubb 9mo ago
  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 9mo ago
    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?
    - LunaSea 9mo ago
      As a data structure it is an ordered list of integers but no LLM needs to accès it in a database, it's way to slow for anything serious. RAG and vector Approximate Nearest Neighbour (ANN) is the the go to use case.
  - thesz 9mo ago
    [1] https://towardsdatascience.com/llm-powered-time-series-analysis/ https://towardsdatascience.com/llm-powered-time-series-analy... [2] https://arxiv.org/abs/2506.02389 https://arxiv.org/abs/2506.02389 [3] https://arxiv.org/html/2402.10835v3 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 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/abstract https://ui.adsabs.harvard.edu/abs/2017EGUGA..19.2950T/abstra...
dangoodmanUT 9mo 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.
- vegabook 9mo ago
  Willing to bet most columnar stores are used for time series.
  - domoritz 9mo ago
    I suspect most use of columnar databases is OLAP, which is different from what people usually mean when they say time series data.
  - goodkiwi 9mo ago
    I’d take that bet
- hodgesrm 9mo ago
  ClickHouse effectively has a number of personas. Time series is one of them, and ClickHouse has steadily absorbed market share from pure play time series databases over the last few years. Other personas include real-time observability backend (the single biggest use case in my experience) as well as real-time data lake engine. Time series support, column storage, and real-time response are key underlying capabilities. It's quite versatile and fun to use. Disclosure: I run Altinity, a vendor in this space. (Update: Disclaimer -> Disclosure. Sigh.)
  - swyx 9mo ago
    Altinity isn't just a vendor, it's THE ClickHouse vendor before ClickHouse became a company. https://altinity.com/blog/big-news-in-the-clickhouse-community https://altinity.com/blog/big-news-in-the-clickhouse-communi... always nice to see a database ceo be "one of us" and/or "write like a real human being".
vibedev 9mo ago
But this is correct? The article that you read is from Langfuse POV, not Clickhouse.
mrits 9mo ago
They are closer to an LLM database than a time series database. But they aren't very close to either.
madduci 9mo ago
Diversification is the keyword

> Our goal continues to be building the best LLM engineering platform Interesting headline for a checks notes time series database company.

by gyre007 9mo ago

> Our goal continues to be building the best LLM engineering platform Interesting headline for a checks notes time series database company.

stingraycharles 9mo ago

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

nsmdkdfk 9mo ago

[dead]

michaelmior 9mo 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-open-source-llm-observability https://clickhouse.com/blog/clickhouse-acquires-langfuse-ope...

cs554 9mo 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)

wodenokoto 9mo 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.

Jgrubb 9mo ago
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 9mo ago
  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?
  - LunaSea 9mo ago
    As a data structure it is an ordered list of integers but no LLM needs to accès it in a database, it's way to slow for anything serious. RAG and vector Approximate Nearest Neighbour (ANN) is the the go to use case.
- thesz 9mo ago
  [1] https://towardsdatascience.com/llm-powered-time-series-analysis/ https://towardsdatascience.com/llm-powered-time-series-analy... [2] https://arxiv.org/abs/2506.02389 https://arxiv.org/abs/2506.02389 [3] https://arxiv.org/html/2402.10835v3 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 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/abstract https://ui.adsabs.harvard.edu/abs/2017EGUGA..19.2950T/abstra...

dangoodmanUT 9mo 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.

vegabook 9mo ago
Willing to bet most columnar stores are used for time series.
- domoritz 9mo ago
  I suspect most use of columnar databases is OLAP, which is different from what people usually mean when they say time series data.
- goodkiwi 9mo ago
  I’d take that bet
hodgesrm 9mo ago
ClickHouse effectively has a number of personas. Time series is one of them, and ClickHouse has steadily absorbed market share from pure play time series databases over the last few years. Other personas include real-time observability backend (the single biggest use case in my experience) as well as real-time data lake engine. Time series support, column storage, and real-time response are key underlying capabilities. It's quite versatile and fun to use. Disclosure: I run Altinity, a vendor in this space. (Update: Disclaimer -> Disclosure. Sigh.)
- swyx 9mo ago
  Altinity isn't just a vendor, it's THE ClickHouse vendor before ClickHouse became a company. https://altinity.com/blog/big-news-in-the-clickhouse-community https://altinity.com/blog/big-news-in-the-clickhouse-communi... always nice to see a database ceo be "one of us" and/or "write like a real human being".

vibedev 9mo ago

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

mrits 9mo ago

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

madduci 9mo ago

Diversification is the keyword