I Built an Open-Source, Self-Hosted Alternative to PostHog on ClickHouse
Per-event pricing can make analytics costs rise with traffic. I built an alternative: SensorFlow — an open-source, self-hosted event analytics stack…
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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…
Deploying SigNoz in 2026: A Survival Guide to ClickHouse v25+ and OTel Gotchas
Hello, fellow developers! 🧑💻 When building a modern B2B SaaS ecosystem, bulletproof observability isn't a luxury—it's a strict survival requirement…
Architecting a Solana Data Pipeline: Economics & System Design
Architecting a Solana Data Pipeline: Economics & System Design If you have ever tried to track every single swap across Raydium, Orca, and Jupit…
От 12 часов к 30 минутам: как мы join’им миллиарды товарных движений в ClickHouse
Всем привет! Меня зовут Муса. Наша команда занимается витринами данных по товарному учёту. Каждый день мы доставляем около 10 млрд записей…
ClickHouse: сценарии, сильные стороны, лучшие практики работы в 2026 году
ClickHouse — один из самых востребованных инструментов для хранения и анализа больших объемов данных, обеспечивающий высокую производительность и на…
ClickHouse: сценарии, сильные стороны, лучшие практики работы в 2026 году
ClickHouse — один из самых востребованных инструментов для хранения и анализа больших объемов данных, обеспечивающий высокую производительность и на…
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 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…
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…
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…
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…
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 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…
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…
PostgreSQL и аналитика: что меняется, когда хранилище становится общим
HTAP — одна из главных тем в мире СУБД. Вокруг PostgreSQL массово появляются конструкции с внешними аналитическими движками со с…
Why Real-Time Analytics Eventually Changes Your Database Architecture
A lot of systems begin with a single database. Usually PostgreSQL. And honestly, in the beginning, that works perfectly fine. The application stores…
DWH в 2026: четыре зоны вместо Inmon, Kimball и Data Vault 2.0
Когда инженер слышит «нам нужно хранилище данных», задача редко звучит однозначно. Кто-то задыхается на боевой OLTP-базе под аналитической нагрузкой…
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 для больших данных: полный гайд по интеграции с NoSQL‑экосистемой
Когда классические SQL‑базы падают под аналитической нагрузкой, а Hadoop‑кластер напоминает чемодан без ручки — пора искать ново…
Why PostgreSQL and ClickHouse Work So Well Together
A lot of people compare PostgreSQL and ClickHouse like they are competing databases. They really are not. In fact, modern data systems often use bot…