Kelly Toole

@ClickHouseDB. prev partner @IndexVentures & eng @Apple. go @Stanford!

[Tanya Bragin @tbragin]

Standing room only at Rows and Columns! After a fiery keynote by @andy_pavlo a panel with @izrailevsky @saileshkrish and @nikitabase starting 🔥🔥🔥

[Andy Pavlo (@andypavlo.bsky.social) @andy_pavlo]

👊I've joined the crew at @ClickHouseDB to establish the *ClickHouse Labs* research group. We'll be working side-by-side with ClickHouse devs to cook up new ways to make the system even faster. I'll also be exploring new topics related to PostgreSQL. https://t.co/7VFLQzAL8g

[ClickHouse @ClickHouseDB]

Welcome to ClickHouse, @andy_pavlo 👋

We're launching ClickHouse Labs, a new research group advancing foundational database technology, led by Andy as VP of Database Research.

Andy is an award-winning database researcher, professor at Carnegie Mellon University’s Computer Science Department and longtime leader of the CMU Database Research Group. At ClickHouse Labs, he'll build a team to take on the hardest problems in database systems, testing their work on real workloads and publishing it in the open, across both ClickHouse and PostgreSQL.

Read Andy’s blog: https://t.co/VO8xYTmfGQ

[Aaron Katz @ceo_clickhouse]

We built a custom sales co-pilot on ClickHouse Agents, and 81% of our sales org uses it every single day to manage accounts worth hundreds of millions of dollars. They're having thousands of conversations that use our data warehouse, salesforce, internal docs and public feeds to support our customers.

We have observability of every conversation via Langfuse, so we can grade answer quality, optimise model selection and pass intelligence to other teams on where sales needs support.

It's built entirely on the ClickHouse Cloud stack using @ClickHouseDB , @LibreChatAI and @langfuse .

[Kelly Toole @ckellytoole]

We’re glad to see @Snowflake engaging with us on cost/performance!

We agree this is one of the most important dimensions customers should evaluate when choosing a data platform, especially as agentic workloads drive higher concurrency, more unpredictable query patterns, and greater pressure on cost.

That’s why we believe benchmarks should be open, transparent, and reproducible. We publish our methodology, code, and results so teams can inspect the setup, run it themselves, and decide what matters for their workload.

We also incorporated @Snowflake’s suggested config changes, reran the benchmark, and found that the price/performance gap actually grew substantially. ClickHouse’s price/performance advantage increased from 22-28x to over 100x for this workload.

To learn more about these latest results, see our blog post below.

https://t.co/oV1DfAi5Bu

[sridhar @RamaswmySridhar]

Hot take: if your benchmark "wins" by omitting half the costs and misconfiguring your competitor's stack, you haven't won anything.

Testing with concurrent workloads at scale reveals Snowflake is far more cost effective than ClickHouse at scale.

More here:
https://t.co/kS0Sbo0Gjz

[Sai Srirampur @saisrirampur]

.@RamaswmySridhar, thank you for engaging here! We read your blog post, incorporated your feedback, and ran the benchmark again.

TL;DR: ClickHouse went from 22-28x to over 100x better price/performance than Snowflake for this workload.

We strongly believe benchmarks should be open, transparent, and reproducible, especially when they’re used to make competitive claims. That’s why we publish the methodology, code, and results behind ours (see the blog post below).

I saw your screenshots above and would welcome the same level of detail on your end so we can understand where any differences are coming from.

https://t.co/tpavqSe9tR

[ClickHouse @ClickHouseDB]

Snowflake responded to our first real-time analytics end-to-end benchmark with some suggestions: use a simpler clustering key, Gen2 hardware, and Interactive Tables.

So, we did all that and ran it again.
https://t.co/iX4ZrKIOJG

[ClickHouse @ClickHouseDB]

As "the yellow company," we have been leading in real-time analytics for years, and believe it to be a foundational workload.

It’s nice to see the other colors finally recognizing it too. 😉

https://t.co/muTZZb0vuK

[ClickHouse @ClickHouseDB]

What did Cisco’s @TalosSecurity get by migrating from OSS to ClickHouse Cloud (and choosing it over Snowflake and MongoDB)?

✅ 90% lower storage costs
✅ 75% lower total cost of ownership
✅ 300+ engineer hours saved per year

Read the full story 👇

https://t.co/DDTHtY3PAI

[Mike Shi — oss/acc @MikeShi42]

Pretty cool seeing the new ClickHouse integration on stage at Datadog Dash this week!

w/ the new integration, teams can keep their favorite data store for high volume logs (ClickHouse!) and work with them from Datadog Log Explorer, ClickStack, and the AI tools they love

[ClickHouse @ClickHouseDB]

ClickHouse is partnering with @datadoghq. Yeah, you read that right. But why?

"We love Datadog, but we don't want to choose which logs to keep."

You've probably heard this before. Maybe you've said it yourself.

That's why we're excited to announce a new partnership with Datadog. You get the Datadog experience you already know, combined with the scale and full-fidelity telemetry retention of ClickHouse.

https://t.co/vlr4a2Xha8

[ClickHouse @ClickHouseDB]

Yesterday we showed the result.

Today we show the engineering behind it.

ClickHouse is 26× faster on TPC-H SF100 after two years of focused join work:
• correlated subqueries
• runtime filters
• lazy column replication
• statistics-based join reordering

https://t.co/ZWC7Dgu3FB

[Tanya Bragin @tbragin]

Could not be more excited to moderate a fireside chat with my personal hero @mipsytipsy at 3pm today @ SF Convene 🔥🔥🔥 Will do my best to make it spicy, but something tells me it will be so regardless 😂

Reg here https://t.co/IPjFwyKt9x

[ClickHouse @ClickHouseDB]

New in ClickHouse Cloud: multi-stage distributed query execution.

https://t.co/wbpSBuIfmo

One query can now be split into distributed stages, with intermediate data shuffled between nodes while it runs.

Large joins and high-cardinality GROUP BYs can now scale with the cluster.

[TechCrunch @TechCrunch]

ClickHouse triples anualized revenue to $250M, charting a path toward an IPO https://t.co/zRYemg3s8o

[ClickHouse @ClickHouseDB]

ClickHouse Open House is live!

Our 2nd annual conference has just started, and we’ll be sharing the biggest announcements, product updates, and highlights right here.

Follow along👇

https://t.co/vMNdl8knfi

[Aaron Katz @ceo_clickhouse]

Next month marks 10 years of @ClickHouseDB as an open source project and we are thrilled to welcome our community at our annual user conference today in San Francisco.

To everyone who contributed code, filed an issue, or ran ClickHouse in production from the beginning: thank you.

Today, we’re proud to share that ClickHouse has over 4,000 customers, passed $250M in ARR, and is trusted by teams like @AnthropicAI, @OpenAI, @cursor_ai, @Lovable, @vercel and many more building the future of AI.

In this post, I cover the milestone, what we’re shipping, and what comes next:
https://t.co/stjs4J3ByA

[Erik Bernhardsson @bernhardsson]

ClickHouse is a very good product imo!

[Marc Klingen @marcklingen]

SaaS is dead, DB is where it’s at. Excited to be part of @ClickHouseDB as we’re the fastest and cheapest.

Just hearing from @iskakaushik and @saisrirampur at our global offsite how we’re the best for all OLTP/postgres workloads as well.

[ClickHouse @ClickHouseDB]

The “Use Elasticsearch for logs” default is starting to look old.

We benchmarked ClickHouse vs Elasticsearch on up to 50B OTel logs: https://t.co/lWjaO3IEYD

ClickHouse:
• up to 6x faster runtimes
• dramatically smaller footprint
• 50B logs ingested in 4 hours vs ~5 days