ClickHouse

. @bulletxyz and @Tristan0x are building DeFi's fastest trading exchange… but their old Databricks/Spark-based analytics stack told a different story. clickhou.se/3RA13dO See how switching to @ClickHouseDB cut query latency 10,000x, improved data freshness from 1-2 hours to <5 seconds, and eliminated an entire serving layer 👇

Postgres page tables scale with connections: on a 32GB shared_buffers, we measured 6.12GB of kernel page tables at 200 connections with 4KB pages, and 111MB with 2MB huge pages, plus 12% more TPS. 🐘 How ClickHouse Managed Postgres configures huge pages, measured on real hardware: clickhou.se/4vXKRSA

Join our free ClickHouse Fundamentals virtual hands-on workshop and learn the core concepts behind one of the fastest databases for real-time analytics and AI. You'll get hands-on experience with: - ClickHouse architecture - Data ingestion and querying - Best practices for your first POC Perfect for engineers evaluating ClickHouse or building their first workload. 📅 July 28 | 9:00 AM IST; 11:30 AM SGT; 1:30 PM AEST 🎟️ Register → clickhou.se/4ffgXSJ

“The age of AI means the age of imagination.” clickhou.se/4fbiqt5 For @insideronehq, an AI-native customer engagement platform, imagination depends on speed. See how they use @ClickHouseDB to power real-time segmentation, analytics, and personalization at scale 👇

P95 latency variance: ±1,580ms → ±60ms. Thanks to the new async-native ClickHouse Python client, which we wrote about back in March. clickhou.se/4am9KyD

InMobi was waiting 60+ seconds for peak-hour reports against a 10-second SLA. clickhou.se/4faFDMk After moving reporting to ClickHouse, P99 dropped under 3 seconds, on a fixed 60 vCPUs and $8k a month instead of $40k.

Agentic analytics lives or dies on time-to-insight. clickhou.se/3R3QGyO @AnthropicAI's Claude Sonnet 5 reasons in tighter steps and gets ClickHouse Agents users to answers noticeably faster. That speed is a difference customers feel. Hear how, live with @zeddotdev: Mon Jul 13, 8am PT 👇

We just shipped our official ADBC driver, in partnership with @columnar_tech. clickhou.se/4gx3nwq One command installs a signed binary, and it speaks Apache Arrow natively, so results move from ClickHouse into your app with zero conversion. Ruby, R, and C get real ClickHouse access for the first time.

ClickHouse is now a Docker Hardened Image: a minimal build that ships only what the database needs to run. clickhouse.com/blog/docker-ha… A standard container trips the vulnerability scanner with 8 medium and 11 low findings, mostly in packages ClickHouse never loads. The hardened image scores 0 medium, because those utilities are gone.

1TB Postgres migration: 17 hours with pg_dump, 1h 50m with PeerDB. We published the how-to a while back. clickhou.se/4vtZBs1

Jakarta, we're back! 🇮🇩 The ClickHouse Indonesia User Group returns on Wednesday, August 5 for an evening of real-world data engineering stories, dinner, and great conversations with the community. On the agenda: 📺 Stream, Ingest, Monitor: Scaling OTT Analytics with ClickHouse by Rafif Abdus Salam, Senior Data Engineer at Vidio. How an OTT platform handles millions of events per minute from edge devices, from streaming and high-volume ingestion to near real-time performance monitoring. ⚙️ Why Real-Time Makes Batch Data Modeling Harder Than Expected by Yunata Gunawan, Data Engineer. Lessons from building a real-time lakehouse: late-arriving events, upserts, versioned records, and why adopting real-time analytics means rethinking your data models, not just your tools. Plus dinner, Q&A, and networking with Jakarta's data community. 🗓️ Wednesday, August 5 | 6:30 PM WIB 📍 GoWork Treasury Tower, 31st Floor, District 8, SCBD, South Jakarta 🎟️ Free, RSVP: clickhou.se/4ylWggO #ClickHouse #DataEngineering #Jakarta #RealTimeAnalytics #OpenSource

Organic slack messages like these make your day. Thank you Dmitrii Tiunov for all the feedback while migrating your primary workload to ClickHouse Managed Postgres. More on the holistic story very soon! Very powerful one - w.r.t. source, scale, metrics etc. 🙏 Many ongoing migrations and customer stories, stay tuned! 🚀 @ClickHouseDB

We caught up with @maverickdotdev to learn how @triggerdotdev is scaling real-time observability for long-running AI workflows, what pushed the team to rethink their database architecture, and why they chose @ClickHouseDB for large-scale observability. clickhou.se/4bxzbO6

Bangkok, we're bringing the data and open source community together! 🇹🇭 Join ClickHouse and LINE MAN Wongnai on Wednesday, July 23 for an evening of talks, demos, and honest conversations about building systems that scale. What to expect: 🍽️ How LINE MAN Wongnai, Thailand's leading food delivery and restaurant platform, tackles data challenges at scale 🔓 Open conversations on the tools, stacks, and ideas shaping the OSS data ecosystem Plus dinner, networking, and plenty of room to meet Bangkok's data community. 🗓️ Wednesday, July 23 | 6:00 PM 📍 LINE MAN Wongnai, One Bangkok Tower 4, Witthayu Rd, Bangkok 🎟️ Free, register on Luma: clickhou.se/4fkTJf5 #ClickHouse #OpenSource #DataEngineering #Bangkok #Observability

Regex in Postgres just got fast. clickhou.se/44RQ3LT pg_re2 adds the RE2 engine (1.8x-8.6x speedup over native functions) and real index support, including a new opclass for trigram indexing across punctuation.

.I've been spending a lot of time thinking about how AI is affecting the data layer. One thing has become increasingly clear to me: AI is fundamentally changing what applications expect from their databases. The traditional boundary between OLTP and OLAP is starting to blur, and the data layer needs to evolve with it. We don't think the answer is forcing unification into a single engine. We think it's bringing together the best transactional database (Postgres) and the best analytical database (ClickHouse), making them work seamlessly for developers. The post dives into why we think this shift is happening, why open source matters more than ever, and the vision we're building toward at ClickHouse. Would love for you to give it a read and get your feedback!

The ClickHouse Delhi User Group is back! 🚀 Join us on Saturday, July 18 for "ClickHouse in the Wild: Architecture Stories from Production," a morning of real-world engineering stories from teams running ClickHouse at serious scale. On the agenda: ⚡ High Speed, Low Latency IoT Logging in ClickHouse by Ashok Vishwakarma, CTO at T9L. How a distributed solar energy grid handles massive telemetry streams from thousands of IoT sensors with sub-second ingestion. 🔄 Beyond CDC: Designing a Point-Read ETL Architecture for ClickHouse by Abhishek Dasgupta, AI Engineer at Zykrr. Why ClickPipes and Debezium-based CDC fell short, and how a Point-Read ETL design migrated 150M+ rows from PostgreSQL to ClickHouse with zero downtime. Plus networking over lunch with the Delhi data community. 🗓️ Saturday, July 18 | 10:00 AM IST 📍 Awfis Space Solutions @ Ambience Mall 🎟️ Free, RSVP required: clickhou.se/3SCeF8L #ClickHouse #RealTimeAnalytics #DataEngineering #Delhi #Meetup

AI is changing more than applications—it's changing the architecture of the data stack. clickhou.se/4p5w99u As AI-native applications generate exponentially more operational data, the traditional boundary between OLTP and OLAP is disappearing. Applications need transactional data to become analytical data in seconds, not hours. We don't think the answer is a single database trying to do everything. We think it's a best-of-breed, open data stack where Postgres and ClickHouse each do what they do best—and work together seamlessly. That's the vision behind our latest piece. Excited to share where we think the future of AI infrastructure is headed