--- collection: data-engineering collection_name: Data & Analytics Engineering week_start: 2026-06-01 title: Executable UDFs and a new dbt core beta lead the week release_count: 10 generated: 2026-07-11 canonical: https://releases.sh/collections/data-engineering/digest/2026-06-01 --- # Executable UDFs and a new dbt core beta lead the week 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](/release/rel_SWzdah-4WwW7pEIwCbxL0-executable-udfs-are-now-in-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](/release/rel_Npr51BEGfBt52g33ILAka-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](/release/rel_EOHHaJVBc54r0V69jGLDC-faster-root-cause-for-slow-traces-with-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](/release/rel_S3w-CBizAFdH1aVXlKbb--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](/release/rel_cCdpDht711lXaHFBmn9ex-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](/release/rel_GQA3mzzusckJraEUPPhJ1-open-sourcing-kubenetmon-how-we-monitor-data-transfer-in-clickhouse-cloud) 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](/release/rel_gHimnfl_ISgzMk-HRC3ms-monitor-slas-and-scale-clickhouse-cloud-with-clickhousectl-and-agents) walks through tagging queries, calculating SLAs, and automating scale decisions. On the Dagster side, [Community Showcase Part 1](/release/rel_LO-HPb39Xwqiw2chMFob6-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 ### ClickHouse - [Executable UDFs are now in public beta on ClickHouse Cloud](https://releases.sh/release/rel_SWzdah-4WwW7pEIwCbxL0-executable-udfs-are-now-in-public-beta-on-clickhouse-cloud) - [ClickHouse Release 26.5](https://releases.sh/release/rel_Npr51BEGfBt52g33ILAka-clickhouse-release-26-5) - [Faster root cause for slow traces with ClickStack Event Deltas](https://releases.sh/release/rel_EOHHaJVBc54r0V69jGLDC-faster-root-cause-for-slow-traces-with-clickstack-event-deltas) - [Open sourcing kubenetmon: how we monitor data transfer in ClickHouse Cloud](https://releases.sh/release/rel_GQA3mzzusckJraEUPPhJ1-open-sourcing-kubenetmon-how-we-monitor-data-transfer-in-clickhouse-cloud) - [Monitor SLAs and scale ClickHouse Cloud with clickhousectl and agents](https://releases.sh/release/rel_gHimnfl_ISgzMk-HRC3ms-monitor-slas-and-scale-clickhouse-cloud-with-clickhousectl-and-agents) ### Dagster - [Community Showcase Part 1](https://releases.sh/release/rel_LO-HPb39Xwqiw2chMFob6-community-showcase-part-1) ### dbt Labs - [dbt-core v1.12.0b2](https://releases.sh/release/rel_S3w-CBizAFdH1aVXlKbb--dbt-core-v1-12-0b2) - [v2.0.0-alpha.1](https://releases.sh/release/rel_cCdpDht711lXaHFBmn9ex-v2-0-0-alpha-1)