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👇 t.co/vMNdl8knfi

Congratulations to @AnthropicAI on raising $65bn. When Claude 3.5 launched, their engineers asked Claude which database to use. Claude recommended ClickHouse. Fast forward a year and we launched ClickHouse Agents. powered by Claude. Here's to building together. t.co/nuosoc1JsZ

Last year, we shared how we saved millions by moving off Datadog and onto ClickHouse. t.co/OvBlatnoHl We scaled our internal observability stack from: 📦 19PB → 100PB 📈 40 trillion → 500 trillion rows 💥 While cutting CPU usage by 90% The key? OpenTelemetry isn’t always the right fit at hyperscale. We implemented a custom pipeline (SysEx) that bypasses OTel and streams ClickHouse data natively. And now with a UI powered by HyperDX for ClickHouse native exploration ⚡

Excited to announce series C financing extension and expansion of the leadership team at ClickHouse! t.co/N8ZFxAa1kr We passed 2,000 customers and more than quadrupled ARR over the past year, adding companies like Anthropic, Cyera, Hewlett Packard Enterprise, Insider, LangChain, Laravel, Masorange, Meta, Qualified, Shopmonkey, Sierra, Supabase, Vercel, Weights & Biases, and many more to the list of organizations building their AI-powered businesses on top of ClickHouse. Many thanks to our new investors: @CitiVentures (@vibhorrastogi), @insightpartners (John Wolff), @peakxvpartners (Shailendra Singh), @FoundersCC (@mikej0000), @DEShawGroup (@jazminsmedina), Adams Street Partners (Fred Wang), @RosbergVentures (@NicoRosberg), @ExpandingCap (@Shriftman), and San Francisco 49s Brock Purdy (@brockpurdy13), Christian McCaffrey (@CMC_22), and Kyle Juszczyk (@JuiceCheck44), and existing investors that participated in this round @AltimeterCap (@jaminball), @BessemerVP (@bdeeter), @IVP (@CackF), @bondcap (Jay Simmons), and GIC (@lihanchen). We're also thrilled to welcome our new executives Kevin Egan (CRO), Mariah Nagy (VP of People), and Jimmy Sexton (CFO). This funding and talent will fuel our mission to empower organizations with lightning-fast analytics on massive datasets in the era of AI.

Congrats to @modal on their $355M Series C! 🎉 t.co/D1gQAzdO46 We wrote last November about the ClickHouse-powered dashboards their customers use to watch AI jobs run in real time - 500B logs, 1–2M events/min, P90 at ~420ms.

Last week, @AnthropicAI raised $30B at a $380B valuation. t.co/nuosoc1JsZ As Claude scales to $14B in annual revenue, its observability infrastructure must handle massive volumes of telemetry data. When Claude 3.5 launched, their previous system couldn't keep up. They built a custom air-gapped ClickHouse deployment that processes AI-scale monitoring data with zero downtime. One engineer's review: "haven't noticed the database running for a while" - the ultimate infrastructure compliment.

Big day at Google Next. t.co/VUcrVJvk2l Four new ClickHouse + Google Cloud milestones: Lakehouse integration, BYOC on GCP, Axion migration, and MCP server support in Google Antigravity.

Congrats to @rdelgado2013 and the rest of the @tryramp team on their $750M raise! It's great to see companies that we work with doing so well. t.co/pv001LYnxN Ryan and his team coined one of our favorite phrases: "Just OLAP it", which is their answer to every slow route or lagging dashboard. It started when Ryan ran ClickHouse against 60 million card transactions. His reaction: "Twelve seconds later, it was done. I've never seen anything like that in my career." 4 weeks later, they were in production with query times reduced from 40+ seconds to milliseconds for 50,000+ customers.

The loudest event at Next ‘26 isn’t a keynote. 🤫 We’re taking over Hakkasan with The Chainsmokers for a night the dev community will be talking about until '27. Data by day. Legends by night. 🪩 Apr 22 | Las Vegas Don't get left in the queue: t.co/n7qiBPcugc

Alexey said it best: “We optimize ClickHouse… and then optimize it again… and again.” t.co/AO8W3A0aY7 25.11 keeps that tradition alive Parallel GROUP BY merges. Projections as true secondary indexes. Faster DISTINCT. More speed everywhere.

We’re bringing Postgres closer to ClickHouse. t.co/LaKGLUdiAv Today, we’re launching a fast, scalable, enterprise-grade Postgres service natively integrated with ClickHouse, designed for real-time and AI-driven workloads. We are partnering with @UbicloudHQ and their world-class Postgres team to bring this offering to life. Read the blog for details and how to join the private preview.

Every second, @canva generates 3M spans + 3M logs for 240M+ users … and those numbers are doubling YoY 🤯 t.co/xVQejrPs0s Their move to @ClickHouseDB delivered: ✔️ 70% cheaper storage ✔️ 10x faster search ✔️ A better logging experience for engineers

When you’re the fastest-growing software company in history, you need a database that can keep up. t.co/CGcC0LJb2Y See how @Lovable uses @ClickHouseDB for large-scale observability, AI-powered debugging, and real-time analytics across millions of user-built apps 👇

One crypto exchange's actual Datadog bill: $65M/year 🤯 t.co/cD8qQ7HiUM The observability industry has built tools that are more expensive than the systems they monitor. It's like paying more for your car's dashboard than the engine. How did this become normal? Mike Shi digs into why this happened: - Vendors built pricing models optimized for extraction, not value - We accepted artificial scarcity (sampling, retention limits) as normal - The same telemetry data gets monetized 3x across metrics, logs, and traces The escape route exists: columnar storage handles wide events efficiently, and OpenTelemetry breaks vendor lock-in. Companies are already cutting costs by 10-100x switching to open architectures. The question isn't whether to migrate—it's how fast you can.

Tesla stress-tested ClickHouse with 1 quadrillion rows. 🤯 The result? No scaling issues. Not a single hiccup. t.co/Vb8pz1FsFx To monitor everything from Gigafactories to millions of connected vehicles, Tesla built a custom observability system—powered by ClickHouse—that: - Ingests tens of millions of rows/sec - Stores trillions of metric samples - Managing tens of billions of unique time series As @alontal put it: “Data in ClickHouse is better than data anywhere else.” Read the full story 👆

The open-source Agentic Data Stack is here 🔥 👉 t.co/bDgxfjdhJy Today, we’re excited to share that we’ve joined forces with @LibreChatAI. Together, ClickHouse and LibreChat form the foundation of the open-source Agentic Data Stack, empowering teams to deploy AI agents that analyze and act on large datasets through natural language. And it’s already powering real-world applications: ⬩@Shopify uses LibreChat internally with 1000+ custom agents and 30+ MCP servers ⬩@DaimlerTruck has deployed LibreChat company-wide for secure AI access ⬩@cBioPortal built a public genomics research agent for cancer data analysis on top of ClickHouse and LibreChat ⬩We deployed a LibreChat-backed agent that now handles approximately 70% of data warehouse queries for over 200 users, processing 33 million LLM tokens daily What doesn't change: ✓ LibreChat remains 100% open source (MIT license) ✓ Community-first development continues ✓ Your existing LibreChat deployments work exactly as before What gets better: ✓ Enterprise-ready features for production agentic analytics workloads ✓ Native LibreChat experience alongside ClickHouse Cloud instances ✓ Extended data visualization support, enterprise-grade security and governance, and a tailored semantic layer The future of data analysis isn't dashboards, it's agents that understand your questions and deliver answers instantly from billions of records. Welcome to the LibreChat team and community! 🎉 Try it yourself 👉 t.co/PeenGvujUt (And by the way, we are hiring. If interested, just ping @ryadhdotnet)

🚀 MongoDB CDC to ClickHouse — Now in Private Preview! t.co/GPesimWoLy In just a few clicks, you can now continuously replicate MongoDB collections (from Atlas or self-hosted) to ClickHouse Cloud and unlock blazing-fast analytics on your document data using the native JSON data type. This powerful integration forms “the Document Data Stack” — combining @MongoDB's high-throughput operational capabilities with ClickHouse’s real-time analytics, on JSON-based document data. It’s perfect for teams building modern web and AI applications that need low-latency transactions and high-speed analytics. What makes this special? • High-performance initial loads + real-time Change Streams • Native JSON data type support: Preserve nested docs, arrays, embedded objects • Enterprise-grade monitoring and alerting • Powered by open-source PeerDB — no vendor lock-in Sign-up for the Private Preview: t.co/cTld2P6utO