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Executable UDFs and a new dbt core beta lead the week

June 1–7, 2026

Executable user-defined functions enter public beta on ClickHouse Cloud, while dbt-core releases its first v2.0.0 alpha alongside a stable v1.12.0 beta. ClickHouse also ships its 26.5 release with record performance optimizations and open-sources a Kubernetes network monitor.

Executable UDFs arrive on ClickHouse Cloud

The week's most practical new capability is executable UDFs entering public beta on ClickHouse Cloud. You can now write a Python function, upload it as a zip to your cluster, and call it from SQL like any built-in. ClickHouse manages a pool of long-lived sandboxed processes and routes rows through them at query speed — meaning the function is callable anywhere SQL is: ad-hoc queries, joins, even materialized views that fire on every insert. This isn't a new idea (executable UDFs have been available in self-managed ClickHouse for a while), but the cloud beta removes the infrastructure barrier. For teams that need custom logic — say, a geocoding step or a regex-heavy transformation — without standing up a separate microservice, this is a direct path.

ClickHouse 26.5: performance at scale

Alongside the UDF beta, ClickHouse Release 26.5 landed with a record 51 performance optimizations. The headline numbers: ORDER BY … LIMIT pushdown through joins can deliver up to 20× faster queries, and a new GROUP BY … LIMIT shortcut avoids building unnecessary groups. There's also a new filesystem table function for running SQL directly against your local file system, which is useful for ad-hoc exploration without an ingest step. For observability practitioners, a companion post on ClickStack Event Deltas explains how to use ClickHouse's lesser-known feature for faster root-cause analysis in slow traces — a practical walkthrough worth reading if you're using HyperDX or building your own observability stack.

dbt-core: alpha meets beta

dbt-core had a bifurcated week. dbt-core v1.12.0b2 brings several quality-of-life features: the maximum seed size is now configurable, and versioned models can automatically create a latest_version pointer (a view aliasing the most recent version of a model) — opt-in via a flag or per-model config. The same day, dbt-core v2.0.0-alpha.1 shipped with a similar latest_version_view feature (reverted and re-added in the same alpha cycle, so expect it to stabilize). The alpha also includes an AI summary for the docs issue workflow. The takeaway: if you need the latest version pointer today, v1.12.0 beta is the stable path; v2.0.0 alpha is worth testing for forward compatibility.

Monitoring and community

Two ClickHouse blog posts round out the week with practical guidance. kubenetmon is a newly open-sourced tool for monitoring data transfer in ClickHouse Cloud — useful if you're running multi-cluster or egress-sensitive workloads. Separately, a guide on using clickhousectl and agents to monitor SLAs and scale walks through tagging queries, calculating SLAs, and automating scale decisions. On the Dagster side, Community Showcase Part 1 highlights creative projects built by the community — from public data exploration to infrastructure monitoring — with notes on why each team chose Dagster.

Releases covered