ClickHouse

A couple weeks ago I co-delivered a talk at ClickHouse's OpenHouse conference on a very interesting Sigma-Clickhouse integration called the "ETL Cache". Like other Sigma caching technology, we're "caching without caching", orchestrating data freshness while never storing any customer data on the Sigma side. If you're curious, check it out here: https://lnkd.in/ghkWpCeG And, if you find these problems interesting and want to help us solve them at Sigma, we're actively hiring for engineers and EMs.

To close out ten years of ClickHouse week, Tyler Hannan wrote an essay about what open source authorship looks like when you take it seriously. 🔹 2,632 contributors ship their names in every build - SELECT * FROM system.contributors and they're right there 🔹 GitHub hit 100,000 combined issues and PRs in March 2026, with a 99% pull request closure rate 🔹 The stained glass argument: every piece stays visible, and the picture only means something when it's all there together https://lnkd.in/ee55xz_7

Earlier this year we put together a walkthrough on building a metrics layer for ClickHouse with MooseStack's open-source QueryModel. The problem it solves: define a metric once and the same number can show up in your dashboard, your API, your MCP server, and your chatbot, but define it four times and they'll disagree within a month. QueryModel keeps a single type-safe definition, tied to your ClickHouse tables, that projects out to every surface from the same code. Each metric is just three parts: an aggregation, its dimensions, and its filters. https://lnkd.in/gadZvR7F

The ClickHouse Open House Roadshow is coming to EMEA this fall! Join us for a day of product deep-dives, real-world use cases, and hands-on workshops, plus plenty of time to connect with the ClickHouse team. Spots are limited, make sure to grab yours now 👇 📍 Amsterdam - September 1 → https://lnkd.in/exAkjE3w 📍 London - September 30 → https://lnkd.in/eKJVJWcG 📍 Munich - October 6 → https://lnkd.in/eTVxaf7U #ClickHouse #OpenHouse #DataEngineering #RealTimeAnalytics #EMEA

🚀 ClickHouse x Confluent 공동 밋업 in Seoul 실시간 분석 플랫폼을 구축하고 계신가요? ClickHouse와 Kafka를 활용해 대규모 데이터를 낮은 지연 시간으로 처리하고, 고성능 분석 서비스를 구현하는 방법을 알아보세요. 이번 밋업에서는: -> Flink와 ClickHouse를 활용한 대규모 실시간 AI -> DelightRoom의 광고 데이터 신선도·정확도 확보 사례 -> ClickHouse와 Kafka 연동을 통한 분석 성능 극대화 ⏰ 6월 30일 오후 6시 30분 📍 스페이스쉐어 강남센터 👇🏼 지금 등록하세요 https://lnkd.in/gP435Jb8 실무 사례와 아키텍처 노하우를 공유하는 이번 기회를 놓치지 마세요! Sunny Yoon Ken Lee Ted Jung #dataengineer #dataengineering #datastreamiing

A few weeks in beta and we've already shipped a round of major updates to Postgres managed by ClickHouse. 🚀 The focus has been on making it easier to operate and more tightly integrated with the rest of ClickHouse Cloud. 🔐 RBAC: fine-grained, per-service access control so teams can collaborate without org-wide admin privileges 🏗️ Terraform provider (alpha) to manage Postgres services alongside your ClickHouse Cloud infrastructure 🔄 ClickPipes: automated Postgres-to-Postgres migrations with built-in schema migration and post-migration automation 💰 Billing live as of June 15 at beta pricing, with detailed usage visible in the ClickHouse Cloud dashboard 💳 Stripe integration for platforms and marketplaces to provision Postgres through their own billing flow 📦 Extensions: smaller binaries, better stability, and faster builds for pg_clickhouse, pg_stat_ch, and pg_re2

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://lnkd.in/gNMqPPxz

Most database benchmarks start at the query. CostBench starts earlier. Ingesting, sorting, indexing, and keeping materialized views fresh all consume time and resources that never show up in a traditional benchmark. So we built CostBench, a new benchmark from ClickHouse that measures the whole path, not just the read step. On June 24th, Tom Schreiber is hosting a free webinar walking through how CostBench works and what it reveals about leading cloud data warehouses. 👉️ Register here: https://lnkd.in/grPriBJB

When METRO Markets GmbH, the B2B marketplace born inside one of Europe's largest retailers, outgrew their self-hosted Hadoop-based stack, they went looking for something faster, cheaper, and more reliable. They chose ClickHouse Cloud over BigQuery and Snowflake. Today, it powers everything from long-term data warehousing and user-facing real-time analytics to credit risk modeling, operational logging, and early AI experiments, all on a single platform. We caught up with Hakan Dilaver, Luis Jurado, and Markus Nutz to learn how a lean data team built a do-it-all data platform that the whole company now runs on. Read the full story 👇 https://lnkd.in/eDy7EeXf