OLAP OVER HTTP: как отдавать большие аналитические данные через API и не положить сервис
Каждый день в 18:00 клиентам становится доступна отчётность по продажам, и многие одновременно нажимают кнопку «Загрузить отчёт». Это может быть дет…
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Never create 1-row ClickHouse parts again: The built-in Buffer Manager.
Day 03 of the WClickHouse Open-Source Engineering Series. You don't need a Redis cluster just to protect ClickHouse from single-event streaming writ…
ClickHouse 26.8 LTS: 57 Breaking Changes Since 26.3
If you run ClickHouse in production, you're probably on 26.3 LTS. And now 26.8 LTS has been announced, which means the LTS-to-LTS upgrade conversati…
От struct к компиляции под схему: ускоряем RowBinary-декодер на Python
Я автор aiochlite — асинхронного клиента ClickHouse на aiohttp . Раньше мой декодер RowBinary читал каждое числовое поле отдельно. Если брать 200 ты…
[Перевод] Предел PostgreSQL: как кеш AI-тестов вырос до миллиарда записей и переехал на ClickHouse
От проблем PostgreSQL к скорости ClickHouse. Рассказываем, как переработали архитектуру кеширования для AI-тестов, чтобы выполнять более 2 млн запро…
Day 96/100 – Standard SQL Time Functions in ClickHouse® 26.3: Better ANSI SQL Compatibility
Introduction One of the key goals of recent ClickHouse® releases has been improving compatibility with the ANSI SQL standard. While ClickHouse has a…
Day 88 - Upgrading to ClickHouse® 26.3 LTS: A Step-by-Step Safe Guide
Introduction Upgrading a database is much more than installing a newer version. It requires careful planning to preserve data integrity, maintain ap…
Day 84: EXPLAIN `pretty=1` and `compact=1` in ClickHouse® 26.3
When a ClickHouse® query runs slowly, the root cause is not always insufficient hardware or an inefficient schema. In many cases, the issue lies in…
Day 71 - Advanced Partitioning Strategies for Petabyte-Scale Tables
As datasets grow into the petabyte range, choosing the right partitioning strategy becomes one of the most important architectural decisions in Clic…
Day 57: Internals of ClickHouse® Data Parts and Merges – A Complete Guide
Introduction One of the reasons ClickHouse® can handle massive analytical workloads with exceptional speed is its storage architecture. Unlike tradi…
Day 50 - How to Migrate Data from MySQL to ClickHouse®: A Step-by-Step Guide
Introduction As applications grow, traditional relational databases such as MySQL may struggle with analytical workloads involving millions of recor…
Шесть недель с agentic AI против фрода в adversarial-системе
Я слишком рано понёс первые результаты в наш продукт. Тогда это выглядело логично: мы прикрутили агентный ИИ к анализу логов и поведения пользовател…
When to denormalize, when to join: A ClickHouse guide (2026)
Denormalization has been the standard approach to analytical data modeling for good reason. Moving joins, lookups, and business rules out of query t…
Day 48 - Sharding Strategies in ClickHouse®
As data volumes grow from gigabytes to terabytes and eventually petabytes, a single database server often becomes a bottleneck. Storage limitations,…
Best real-time analytics database for star schema and fast joins (2026 guide)
Modern OLAP databases like ClickHouse now handle star schemas and complex cross-table joins at massive scale. That gives data engineering teams a re…
Day 41: Monitoring ClickHouse® Performance Metrics
Monitoring ClickHouse® Performance Metrics Introduction Monitoring is a fundamental part of operating a healthy ClickHouse® deployment. As databases…
Day 28 of 100 Days of ClickHouse® – Understanding TTL (Time To Live) for Automated Data Lifecycle Management
Introduction As data grows over time, storing every row forever becomes increasingly expensive and often unnecessary. Application logs, IoT events,…
Day 25 of 100 Days of ClickHouse: Mastering the ClickHouse HTTP API
ClickHouse HTTP API: A Complete Beginner's Guide Introduction When most people think about interacting with a database, they usually imagine connect…
Why ClickHouse Merges and Mutations Are Difficult to Track in Production
One of the reasons ClickHouse delivers exceptional analytical performance is its ability to optimize data in the background. While users focus on wr…
Why Audit Trails Matter in ClickHouse®: Building Accountability, Compliance, and Security
When teams evaluate database platforms, the conversation usually revolves around performance, scalability, query optimization, and storage efficienc…
SELECT FINAL and OPTIMIZE FINAL Are Not the Same Thing
One thing that confused me when I first started learning ClickHouse was the word FINAL . Because eventually you'll come across both: SELECT * FROM e…
100 Days of ClickHouse® – Day 6: Importing CSV Files into ClickHouse®
CSV files are one of the most common formats for storing and exchanging data. Whether you’re working with logs, analytics data, application exports,…
Replicate MySQL to ClickHouse with Sling
Introduction ClickHouse is a columnar OLAP database. It runs aggregate queries across billions of rows in seconds. MySQL is what most apps run on fo…
Four LLM Engines, One ClickHouse Cluster: An Agentic AI Architecture
We are building an agentic AI analytics platform for a crypto exchange where internal teams — Trading Ops, Risk, Compliance, Finance, Treasury, Prod…
ClickHouse JOINs Aren't Slow Anymore (You're Reading 2020's Docs)
ClickHouse JOIN performance was rebuilt between 2022 and 2026. The "avoid JOINs in ClickHouse" advice from 2020 is still circulating: "ClickHouse ca…