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title: Andy Pavlo Joins ClickHouse to Establish ClickHouse Labs
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# Andy Pavlo Joins ClickHouse to Establish ClickHouse Labs

**[Hacker News](https://daily.dev/sources/hn)** · 4 min read · 0 upvotes · 0 comments

## Summary

Andy Pavlo, Carnegie Mellon University database professor, is joining ClickHouse to establish ClickHouse Labs, a new industry research organization focused on database systems. The lab will work closely with ClickHouse engineers rather than operating in isolation, aiming to accelerate validation of existing ideas and explore new ones. Research priorities include improving ClickHouse's core DBMS, supporting ClickHouse's PostgreSQL managed service, and investigating how databases fit into emerging AI and agentic technologies — both how DBMSs can better support AI agents and how agents can improve DBMS development itself.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://clickhouse.com/blog/andy-pavlo-joins-clickhouse>

## Community take

How the wider developer community reacted, aggregated from 1 discussion and 61 comments across hackernews (as of 2026-08-04).

**TL;DR:** The community is broadly positive about Andy Pavlo joining ClickHouse, celebrating his CMU lecture series and database expertise, while a side debate erupts over whether database research qualifies as 'deep tech' and what a corporate research lab actually means in practice.

**Sentiment:** 65% positive · 25% mixed · 10% skeptical

**The case for**

- Andy Pavlo's CMU lecture series (15-445) is widely praised as a high-quality, freely accessible resource that has helped many developers break into database engineering.
- Having a research lab embedded with engineers rather than isolated is seen as a smart model, with IBM Research Almaden and Microsoft Research cited as good precedents.
- Commenters see this as a positive signal that ClickHouse is investing in fundamental infrastructure research outside the AI hype cycle.
- Several open database research problems (indexing, cache replacement, exabyte-scale internals) are highlighted as genuinely hard and worth pursuing.

**The pushback**

- Some skeptics question whether a company-embedded 'research lab' is meaningfully different from just hiring engineers to work on the product.
- Concern raised that industry research labs can stifle broader company innovation by concentrating exploratory work in one group.
- A commenter urged ClickHouse to also fund academic DB research, noting government funding for databases has nearly dried up amid the AI funding wave.

**By community**

- hackernews (positive): Mostly enthusiastic about Pavlo's move and his CMU course legacy, with a lively but tangential debate about whether databases count as 'deep tech' and what corporate research labs actually do.

**Hottest debate:** Whether database research qualifies as 'deep tech' in the traditional sense versus being important-but-incremental engineering work on already-existing systems.

**Open questions**

- Will Andy Pavlo maintain his CMU affiliation and continue the open lecture series?
- Will ClickHouse fund external academic database research, given the collapse of government DB research funding?
- How will ClickHouse Labs differ in practice from simply having senior research engineers embedded in the product team?

**Highlights**

> There are several interesting foundational problems around scalability, generality, efficiency, and adaptability. Historically use cases haven't always been there to justify focusing on these problems but that is changing. In my opinion, some of the more important open problems: Ideally a table should be index-organized across all relevant columns. No public system works anything like this. We don't have single indexing structures that work for a collection of arbitrary types each with possibly unpredictable distributions, never mind ones that mix temporal, geometric, and other difficult types. The AI-complete nature of indexing becomes evident when you dig into this. Downstream from this is an implication of extremely granular and adaptive storage management that current storage engines aren't designed for. Tractable cache replacement algorithms are broken for many workloads and data models. These algorithms need to be very fast for search, update, and eviction selection but they are also AI-complete; improvements to generality have impractically high computational cost. Storage growth is decoupled from RAM availability thanks to disaggregation, aggravating the problem even for workloads that worked well under tractable cache replacement. In theory we know that cache admission (read: fancy latency-hiding schedules) is more robust and scales better but is so difficult to implement in non-trivial real systems that I don't think anyone has figured out how to reduce that concept to practice yet. At exabyte scales, conventional database internals have embedded assumptions that no longer hold true. For example, you cannot guarantee even "small" internal control structures are resident in memory. What used to be fairly boring internals bits in databases suddenly have to be redesigned from first principles. This is more applied than theoretical but it suggests a major change in the way we do internal architecture. Traditionally we've treated spatial and temporal locality as architecturally separate concerns. This is extremely convenient from a building real systems standpoint. Optimizing either one in isolation is adversarial to the efficiency of the other, which becomes increasingly visible as you scale up. Converging these concerns into a single "thing" almost certainly has solving the above problems as a prerequisite. If you squint, you can kind of see this as the last step before databases become literal AI. All of these have really broad scope. If we could solve even half of these open research problems the resulting database engines would be unrecognizable. There are ton of other narrower interesting research problems around data layouts, compression, join parallelism, etc that still have potential for substantial improvement. It is a great time to be doing database research, we've barely scratched the surface.
> — [jandrewrogers on hackernews · 1 comments](https://news.ycombinator.com/item?id=49160322)

> They will continue. New seminar series starts next month (announcement coming this week).
> — [apavlo on hackernews · 3 comments](https://news.ycombinator.com/item?id=49157821)

> I “audited” CMU 15-445 in April 2026, a few months ago. I then applied to Azure Hyperscale DB team, and as my pitch to get hired I cold DM’d the hiring manager whatever I finished in the assignments (BPM, Concurrent B-tree, Transaction support etc). With that, I was able to get the interview although I ended up failing it. My lack of experience in C++ was probably one of the main reasons. Your course helped me stand my own during the interview and even though I had zero database experience apart from finishing the course, I felt adequately prepared. Thank you for making the course open source. As a working professional, it was helpful to be able to do the course on my own time. Suffice to say, I am a big fan of your work and thank you for introducing me (and other fellow learners) to the interesting world of Databases!
> — [AbbeFaria on hackernews · 1 comments](https://news.ycombinator.com/item?id=49158911)

> Its refreshing to see corporate research labs in a non AI area. Clickhouse has been a huge beneficiary of the AI wave and its good to see some of the value going into advancing fundamental research in infrastructure
> — [adi2907 on hackernews](https://news.ycombinator.com/item?id=49162974)

> Andy was a PhD student at Brown when I was an undergrad. Once he hired a magician off of Craigslist for a departmental event. The guy showed up drunk and lost his bird in the building.
> — [bhickey on hackernews](https://news.ycombinator.com/item?id=49163880)

**Source threads**

- [hackernews](https://news.ycombinator.com/item?id=49156011) · 277 points · 61 comments

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---

Tags: [#backend](https://daily.dev/tags/backend), [#postgresql](https://daily.dev/tags/postgresql), [#clickhouse](https://daily.dev/tags/clickhouse)

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