Case Study: HIFI accelerates royalty data analytics with ClickHouse

HIFI’s migration from BigQuery to ClickHouse

HIFI is building financial and business insights for music creators and rights holders, and needed a way to process massive, fragmented royalty datasets quickly and reliably. After struggling with BigQuery’s cost structure and performance limitations, HIFI turned to ClickHouse to store and organize royalty data for HIFI Enterprise, where a single account can contain over 25 million rows of streaming and transaction data.

Using ClickHouse, HIFI was able to speed up dashboard loads dramatically, with its largest datasets now loading in under a few seconds even with caching turned off. ClickHouse also helped HIFI run internal royalty metrics faster and handle complex joins more efficiently through ClickHouse-specific optimizations, improving the user experience and supporting future scale.

HIFI

John Funge

Chief Technology Officer