Case Study: Datavations cuts costs and speeds up analytics with ClickHouse

How Datavations rebuilt its pipeline with ClickHouse

Datavations, a New York-based data and optimization platform for the home improvement industry, needed a faster and more cost-effective way to process massive store-level data as it scaled. Its earlier stack built around S3, Databricks, Athena, and Tableau became expensive and slow, creating lag in data quality checks and analyst workflows.

Datavations rebuilt its pipeline with ClickHouse, using Kinesis Firehose, AWS Glue, ClickHouse’s S3 table engine, and separate processing and analytics instances to split transformation from end-user queries. With ClickHouse, the company reported a 15x reduction in cloud costs, 18x faster processing, and a 5x efficiency boost for analysts, while compression reduced 42 TB of uncompressed data to 1.66 TB and cut SLA turnaround from days to hours.

Datavations

Jacob Lucas

Co-Founder and Head of Engineering