Search headlines, summaries and articles to connect the dots.
ClickHouse Security, an agentic SIEM built on RunReveal and ClickHouse Cloud, is now in private preview, with AI agents, 100+ integrations and built-in detections running on your own ClickHouse service.
One open source entry point for all AI usage in your company. See every model call, who made it and what it cost, natively traced in Langfuse.
Your observability UI shouldn't limit the questions you can ask. Explore how ClickHouse Observability Apps turns a prompt into custom investigation experiences, why SQL makes it possible, and what we still need to get right.
Hidehiko ASAHI shares a month of WalShadow private-preview testing, comparing replication latency with ClickPipes and checking data correctness, schema changes, and recovery.
AI adoption moves fast. Readiness takes longer. Assess 6 dimensions to see where your data foundation limits AI.
Jev ranks warehouse tables and labels agent failures in under a second, but adding retrieval hints leaves accuracy flat across 20 models on the Agentic Analytics Benchmark.
ClickHouse’s new exhaustive cost-based join optimizer safely reorders inner, outer, semi, and anti joins to find the cheapest valid plan.
Google Cloud on wiring BigQuery's AI SQL functions into dbt pipelines, from sentiment scoring to LLM-generated product briefings.
Most models in a dbt DAG aren't on the critical path. Espresso AI and Authentic Insurance on turning that slack into real savings.
Ecolab and Datafold used an AI migration agent to rebuild a decade of tangled Snowflake logic as clean, documented dbt models.
Checkr gave its AI agent a structured dbt context layer, cutting a support-metric investigation from hours to minutes.
Why conversational analytics stalls and the data fundamentals that make it reliable.
Why AI agents can make semantic layers stick, if teams can solve the trust problem.
Okta rebuilt how it governs context for AI agents, using dbt as the single source of truth.
dbt v2 bundles adapters, speeds up parsing, and replaces manifest.json with smaller, queryable files for people and AI.
We ran one AI skill 80 times against four context sources. Engineered summaries cut cost 48.5% and run time 43.2%.
How a data scientist built an AI context layer for organizational knowledge a dbt project alone can't hold.
Connect Cursor to Langfuse to trace every agent turn, pinpoint expensive model and tool calls, and use evaluations to confirm a fix actually helps, with ClickHouse powering the analytics underneath.
We added GPT-6 Astra, Luna and Sol, Claude Opus 5.5 and Claude Sonnet 5.5 to the Agentic Analytics Benchmark: all five land mid-board within a point of each other, and Sonnet 5.5 brings the biggest change in turns, cost and truncated runs.
ClickHouse’s new native TCP client for .NET brings faster reads and inserts with fewer allocations, columnar APIs, POCO support, and a path to migrate from HTTP.
