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March 2026 newsletter

Mark Needham
Mar 19, 2026 · 9 minutes read

Hello, and welcome to the March 2026 ClickHouse newsletter!

This month, we have an overview of Geospatial, the launch of chDB 4, how Hookdeck made payload search 60 times faster, The Agentic Data Stack, and more!

Featured community member: Jamie Herre #

This month's featured community member is Jamie Herre, Sr. Director of Engineering at Cloudflare.

Jamie leads engineering on Cloudflare's analytics infrastructure - a system that processes over 1.61 quadrillion events every day across more than 300 global data centers, built on ClickHouse.

At the ClickHouse meetup in August 2025, Jamie shared how his team designed for both explosive growth and catastrophic failure simultaneously. In one live demonstration, a single query scanned 96 trillion events in under 2 seconds - while a simulated North American outage caused European clusters to silently absorb the load without missing a beat.

➡️ Connect with Jamie on LinkedIn

Upcoming events #

Global virtual events #

Virtual training #

Events in AMER #

Events in EMEA #

Events in APAC #

26.2 release #

My favorite feature in the recent ClickHouse 26.2 release is time-based block flushing for streaming data. This lets you batch inserts by time interval rather than row count, which is useful for low-throughput feeds like Wikimedia recent changes.

The release also brings production-ready text index and QBit data types, 3.2x faster RIGHT/FULL JOINs, and embedded ClickStack for in-product observability.

➡️ Read the release post

Building towards an enterprise-grade Postgres service in ClickHouse Cloud #

Sai Srirampur introduces the enterprise-grade Postgres service, coming soon to ClickHouse Cloud, bringing cross-AZ high availability, point-in-time recovery, automated backups, and failover-safe CDC slots for ClickHouse integration.

In other Postgres news, Kaushik Iska introduces pg_stat_ch, an open-source Postgres extension that streams query metrics directly into ClickHouse for latency analysis and error tracking without impacting production performance.

➡️ Read the blog post

Announcing chDB 4: Write Pandas, Run ClickHouse, Now on Hex #

Ryadh Dahimene and Auxten Wang introduce chDB 4, which adds a Pandas-compatible DataStore API that executes on ClickHouse's engine under the hood.

Operations run lazily as an optimized pipeline, with automatic routing between ClickHouse and Pandas engines, and it's now available natively in Hex notebooks.

➡️ Read the release post

How Trigger.dev built a custom SQL language on top of ClickHouse #

Matt Aitken, CEO of Trigger.dev, explains how they gave users SQL access to a shared multi-tenant ClickHouse cluster without risking data leaks.

Their solution is TRQL, a SQL-style DSL that compiles to tenant-isolated ClickHouse queries - dangerous operations are grammatically impossible, and tenant filters are injected at compile time.

➡️ Read the blog post

Announcing General Availability of ClickHouse Full-text Search #

Melvyn Peignon announces the general availability of full-text search in ClickHouse, which uses native inverted indexes to enable fast token-based filtering at scale.

The implementation supersedes Bloom filters for string matching, delivering deterministic results without false positives and reducing the number of granules scanned by up to 96%.

To see it in action, Lionel Palacin built GitTrends, an open-source demo that searches and aggregates nearly 10 billion GitHub events in real time, with a live comparison tool showing the performance differences between full-text search, Bloom filters, and a full table scan.

➡️ Read the blog post

How we made payload search 60x faster in ClickHouse #

Maurice Kherlakian at Hookdeck describes how webhook payload search across millions of semi-structured JSON records was timing out at 30+ seconds, making debugging nearly impossible.

The fix: hashing values into typed bucket columns so queries scan a single bucket instead of all, combined with iterative time-window scanning that stops once enough results are found, bringing latency down to under 400ms.

➡️ Read the blog post

The Agentic Data Stack #

Dustin Healy outlines an open-source agentic data stack that lets AI agents query ClickHouse directly via natural language, replacing dashboards and data tickets with real-time conversational access.

The architecture combines ClickHouse's MCP server with an open-source LLM interface and Langfuse for observability, keeping data and infrastructure under the user's control.

➡️ Read the blog post

ClickHouse TTL in production: A safe strategy for data retention and disk optimization #

Aliakbar Hosseinzadeh shares a production runbook for implementing ClickHouse TTL policies after his cluster hit 97% disk utilization, covering the key mental model shift: TTL runs during background merges, not at insert time.

The winning combination is to align partitioning with your TTL time unit and set ttl_only_drop_parts=1, which lets ClickHouse drop whole parts cleanly rather than triggering expensive mutation-style rewrites.

➡️ Read the blog post

Quick reads #

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