Data Modeling Guide for Real-Time Analytics with ClickHouse

Summary

This article was written as part of my services Querying billions of weather records and getting results in under 200 milliseconds isn’t theory; it’s what real-time analytics solutions provide. Processing streaming IoT data from thousands of sensors while delivering real-time dashboards with no lag is what certain business domains need. That’s what you’ll learn at the end of this guide through building a ClickHouse-modeled analytics use case. You’ll learn how to land data in ClickHouse that is optimized for real-time data applications, going from basic ingestion to advanced techniques like statistical sampling, pre-aggregation strategies, and multi-level optimization. I’ve included battle-tested practices from Rill’s years of implementing real-time analytics for customers processing everything from financial transactions and programmatic advertising to IoT telemetry. This article is for data engineers and practitioners who want to build analytics that deliver sub-second query responses, and who want to unlock ClickHouse’s full potential for real-time analytics demands. By the end, you’ll have a playbook for ClickHouse data modeling plus a working example that ingests NOAA weather data from S3 and visualizes it with a single configuration file. Why ClickHouseIf you haven’t heard of ClickHouse or are wondering why it’s becoming the go-to choice for real-time analytics, here’s what sets it apart from traditional data warehouses. ClickHouse achieves blazingly fast analytical performance through column-oriented storage that reads only relevant data, advanced compression (LZ4/ZSTD), and vectorized query execution that maximizes CPU capabilities. Its sparse primary indexing with data skipping eliminates irrelevant data blocks, while the C++ implementation avoids JVM overhead for bare-metal performance. These innovations enable sub-second query responses on billions of rows, performance that would take minutes or hours in traditional data warehouses. Storage efficiency has ...