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 ClickH…
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Postgres vs ClickHouse? I use both. 4 tricks from the split.
TL;DR. My uptime monitor keeps config and incidents in Postgres and check results in ClickHouse. The split is one rule: does a row ever change? Config…
Day 64: ClickHouse® Query Cache – Configuration, Best Practices, and Common Pitfalls
Introduction Analytical platforms often execute the same SQL queries repeatedly. Business Intelligence (BI) dashboards refresh every few minutes, sche…
Day 63: Advanced ClickHouse® Dictionaries – Integrating External Data Sources for Faster Lookups
Introduction Modern analytics platforms rarely store all business data in one place. Customer information may reside in PostgreSQL, product catalogs i…
Пока все хоронили пайплайны, ClickHouse достраивал слои
«Отдельные базы больше не нужны», «конец пайплайнов» - каждую неделю кто-то крупный со сцены хоронит то, что ты вчера поставил в прод. ClickHouse пост…
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 traditi…
Day 53: ClickHouse® Data Sampling Explained – Query Billions of Rows Faster
ClickHouse® Data Sampling: Querying Billions of Rows Fast Day 53 of #100DaysOfClickHouse Modern analytics platforms routinely manage billions—or even …
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 records…
Databricks обещал конец баз данных. Читаем мелкий шрифт
Пару дней назад я собрал сводку новостей по lakehouse и закончил её обещанием: разберу каждый громкий анонс по отдельности. Выполняю - и начинаю с сам…
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 пользователей…
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 tim…
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, C…
Day 44 – Exploring ClickHouse® System Tables for Troubleshooting
Introduction ClickHouse® provides a rich collection of built-in system tables that expose valuable information about the server's internal operations.…
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 real…
Day 41: Monitoring ClickHouse® Performance Metrics
Monitoring ClickHouse® Performance Metrics Introduction Monitoring is a fundamental part of operating a healthy ClickHouse® deployment. As databases g…
Как мы ушли от ETL к CDC: выбираем архитектуру real-time аналитики на PostgreSQL, Kafka и ClickHouse. Часть 1
Все началось с просьбы сделать отчеты в реальном времени. На первый взгляд задача выглядела простой, но довольно быстро выяснилось, что существующая а…
Day 35 – ClickHouse® and S3 Integration: Querying Data Lakes
Introduction Modern organizations generate massive amounts of data that need to be stored and analyzed efficiently. As data volumes continue to grow, …
Day 33: Understanding ClickHouse® Query Execution Plans
Introduction When a query runs in ClickHouse®, the database does much more than simply read data and return results. Before execution begins, ClickHou…
Реалтайм-аналитика «без боли»: миграция из PostgreSQL и Kafka в ClickHouse и визуализация в Superset
Когда у вас появляется продукт с активными процессами и большим количеством пользователей, объём данных начинает расти быстрее, чем ожидалось. На стар…
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, mo…
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 connectin…
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 writ…
Технический и продуктовый мониторинг за кастомизациями Битрикс24: как настроить и на что смотреть
Рассказываем и показываем, как можно использовать мониторинг за кастомизациями Битрикс24. Для работы используем телеметрическую инфраструктуру на базе…
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 efficiency.…
Postgres or ClickHouse? Row vs Column Storage, and When Each Wins
PostgreSQL and ClickHouse both speak SQL, both call themselves databases, and both will happily store your data. That surface similarity gets teams in…
Day 17 of #100DaysOfClickHouse: Mastering Data Filtering for Faster ClickHouse Queries
When working with ClickHouse®, writing a query is usually straightforward. Writing an efficient query, however, requires understanding how ClickHouse …
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 eve…
Day 14 of #100DaysOfClickHouse: Understanding Nodes, Shards, and Replicas
When people first start learning ClickHouse®, they usually focus on SQL queries, table engines, and performance optimization. But as data grows from m…
Внедрение SQLMesh в команду аналитики
Каждая команда аналитики рано или поздно сталкивается с одной и той же проблемой: SQL-скрипты начинают жить своей жизнью, lineage оказывается неполным…
Как мы собрали систему сетевого мониторинга безопасности для ISP: Zeek, Suricata, OpenSearch и ClickHouse
Мы построили собственную систему мониторинга сетевой безопасности для интернет-провайдера. Она в реальном времени анализирует трафик, помогает видеть …