Snowflake has released details of a data modernization project it says helped Booking.com address performance issues during peak travel periods and improve how internal teams discover and manage data.
In the case study shared by Snowflake, the company said Booking.com operates at very large scale, serving “hundreds of millions of users across 220 countries and territories.” Snowflake added that Booking.com’s prior Hadoop-based data ecosystem struggled to keep up during high-demand seasons, leading to workload delays and making it harder for teams to locate the right datasets.
According to the vendor, Booking.com migrated to Snowflake to run analytics workloads more efficiently. Snowflake stated that the company’s teams process workloads across “31 million listings” after the migration and that they can do so “without bottlenecks.”
Self-service discovery and governance
Snowflake also described changes to how Booking.com’s employees work with data after the migration. The vendor said employees are able to discover and explore data on their own, rather than relying on manual processes to find information.
On governance and compliance, Snowflake claimed that “native governance” can handle GDPR-related requirements and help support compliance with the EU AI Act, reducing the need for manual oversight. Snowflake did not provide additional implementation details in the release.
Vendor claims presented as a case study
The information comes from Snowflake’s described case study about Booking.com’s data-stack modernization. Snowflake positioned the project as an example of how analytics performance and internal data workflows can be improved by moving from a Hadoop ecosystem to Snowflake.
The release did not include independent verification, third-party performance benchmarks, or specific technical metrics beyond the listing scale and qualitative outcomes described by Snowflake.
