How ClickHouse Uses SQL

ClickHouse Grafana plugin 4.20 brings compact query mode, click-to-filter log investigation, guided variable and annotation editors, and OpenTelemetry dashboards

iFood rebuilt its in-house security platform on ClickHouse Cloud, getting 9-16x faster queries at 40-50% of the cost and unlocking agentic threat hunts that cut a week of analyst work down to two hours.

Explore ClickStack’s latest upgrades, from richer trace navigation and Prometheus connectivity to smarter dashboards, quieter alerts, faster filtering and support for exponential histogram metrics.

This release brings speedups for GROUP BY ... ORDER BY ... LIMIT, three JOIN improvements, four vector search improvements, position-aware phrase search, EXPLAIN ANALYZE, unified URL access, and more!

Physical Intelligence runs both its OLAP and OLTP workloads on ClickHouse managed Postgres and ClickHouse Cloud

How we rebuilt ClickHouse Cloud's autoscaling orchestration on Kubernetes' controller-runtime and a ClickHouse-powered signals table, adding a reactive fast path that scales services up in seconds instead of waiting for the next scheduled pass.

You can choose any of these hundred database systems and run queries. You can create tables and databases, insert data, drop tables, etc. Every database comes with a preloaded dataset of 100 million records, so you can test example queries. It has not onl

Using ClickHouse for observability and wondering which interface best fits your workflows? We explore ClickStack, Grafana, and when it makes sense to use both.

Why ClickHouse Managed Postgres runs strict memory overcommit by default, and how it turns an instance-wide OOM restart into a single failed query — shown side by side on identical hardware, with no measurable throughput cost.

A behind-the-scenes look at hdx-evals, the open-source framework we built to benchmark the ClickStack MCP server against a raw SQL baseline using deterministic synthetic incidents, sandboxed Claude agents, and blind LLM grading — and why the MCP scored hi

How a coding agent used clickhousectl to stand up a distributed ClickStack across the US, Europe, and Japan, with regional ingestion and one global view.

January’s ClickStack update brings Managed ClickStack, dramatically faster text search with new indexing options, materialized view powered alerts, and a wave of usability upgrades across the stack.

Using ClickHouse as a webhook endpoint with HMAC verification

Search and uncover technology trends across 10 billion GitHub events in real time.

Februarys' ClickStack update brings major improvements to both Cloud and open source, including new query workflows, enhanced metrics exploration, performance optimizations, and expanded alerting options.

This post shows a lightweight metrics layer for ClickHouse using MooseStack, an open source developer agent harness for ClickHouse.

ClickHouse is fast by design, but raw database speed isn't enough. This post explores how ClickStack tightly integrates with ClickHouse to generate optimized queries — from progressive time window pagination and chunked charts to automatic use of materi

Learn how to send structured .NET logs directly to ClickHouse using Serilog — with full schema control, full-text search, and SQL queries over your log data.

High-performance full-text search, even on object storage. This deep dive from the ClickHouse engineers explains the new text index design and how it keeps queries fast at scale.

Ten best practices for getting the most out of ClickHouse, from primary key design and data types to materialized views, ReplacingMergeTree, and join optimization — illustrated with benchmarks on a 150M row dataset.

ClickStack now supports Role-Based Access Control, giving teams precise control over who can access dashboards, searches, and notebooks. With flexible roles, fine-grained permissions, and seamless ClickHouse Cloud integration.

How to remain competitive in the AI era of software engineering

Retention limits, sampling, and metric roll-ups aren't observability best practices - they're workarounds for storage systems that can't handle full-fidelity data, and they're becoming a hard blocker for AI-driven workflows.

A Solutions Architect’s experience building a retail analytics platform with AI agents, real-time dashboards, and full observability on the ClickHouse data platform

ClickStack’s March release introduces smarter Event Deltas, AI-powered notebooks, and full SQL chart flexibility, making investigation faster and dashboards more powerful.

We see ClickHouse and Grafana as a key part of the observability experience. Here's our vision for making the plugin more powerful and easier to use.

ClickHouse now brings full-text search and large-scale analytics together in one engine, making it a powerful alternative to Elasticsearch for log analytics. This benchmark shows why.

We use clickhousectl to spin up multiple ClickHouse versions side by side and benchmark two recent performance improvements.

Agentic analytics makes query-readiness a write-side cost problem. This post compares Snowflake and ClickHouse under continuous ingest, showing how ClickHouse obtains query-ready data at 22× lower cost and delivers 31× better write-side cost-performance.

ClickHouse 26.4 is here! In this release, more features become SQL compatible, COUNT DISTINCT gets faster, EXPLAIN gets even prettier, and more

Learn how ClickStack’s new SQL-powered charting and alerting unlock anomaly detection, rolling baselines, and advanced observability workflows directly on top of ClickHouse, without relying on external tooling.

A deep dive into how pg_clickhouse's Foreign Data Wrapper decides what SQL to push down to ClickHouse versus execute locally in Postgres .

In this blog, we explore why high cardinality behaves fundamentally differently in column-oriented databases like ClickHouse, and why the costs appear in very different places than in traditional series-based systems like Prometheus.

ClickStack’s April release

How we integrated the Rust Delta Kernel to replace our native Delta Lake implementation, reducing maintenance overhead while unlocking writes, schema evolution, time travel, and partition pruning.

ClickHouse Cloud introduces multi-stage distributed query execution, a new foundation for scaling single queries across many nodes and accelerating large joins and high-cardinality aggregations.

Introducing CostBench, an open benchmark that turns cloud data warehouse runtime and billing models into comparable performance-per-dollar results.

ClickHouse 26.5 is here! In this release, we have a record number of performance optimizations, a new `filesystem` table function for querying your local file system with SQL, and more!

ClickHouse Cloud takes on Snowflake, Databricks, BigQuery, and Redshift on TPC-H, ranking first on SF100 cost-performance and running SF10 for less than one cent.

A walkthrough of building a .NET API gateway with YARP and Aspire that logs every proxied request to ClickHouse for aggregate analytics, with a materialized view keeping dashboard queries fast as traffic grows.

A walkthrough of adding OpenTelemetry instrumentation to two ASP.NET services — an Order API and a Payment Service — and shipping traces, logs, and metrics to ClickStack, with auto-correlated signals and cross-service trace waterfalls out of the box.

Over two years of focused join engineering, ClickHouse became 26× faster on the TPC-H SF100 join-heavy workload. Here’s how parallel hash joins, runtime filters, lazy column replication, and smarter join planning got us there.

ClickHouse was released in open source on Jun 15 2016, ten years ago. Since then, it became the most popular open source analytical database with more than 2000 contributors.

On June 15, 2016, ClickHouse went open source under the Apache 2.0 license. Ten years later, it's one of the most widely deployed analytical databases in the world.

We’ve shipped dashboard actions, custom number palettes, flexible event patterns, a built-in RUM experience, major trace view improvements, expanded MCP capabilities, scoped dashboard filters, and much more in ClickStack this May.

ClickHouse 26.6 is here! In this release, we have hypothetical skip indexes, cascading refreshable materialized views, experimental support for continuous queries, and more!

chDB embeds a full ClickHouse query engine inside an agent's own process, turning data access, memory, and federation into local function calls instead of network round trips, cutting the latency, retries, and token waste that come with remote queries.

ClickHouse now has an official ADBC driver, giving Ruby, R, C, and every other ADBC-aware tool zero-conversion, Arrow-native access to ClickHouse without a dedicated client for each language.

A hands-on walkthrough of loading billions of Binance tick records into ClickHouse, showing how columnar storage and codecs compress trade and quote data 19x, and how standard SQL handles VWAP, OHLC candles, and as-of joins at millisecond granularity.

Welcome to the July 2026 ClickHouse newsletter, which will round up what’s happened in real-time data warehouses over the last month.