ClickHouse vs BigQuery

- Yes
Up to 95% faster querying speeds and 60% less storage space required.
- Yes
Up to 100x more cost-effective.
- Yes
Standard SQL enhanced with numerous extensions and improvements (e.g. lambda functions and higher-order functions), that make analytical tasks very user-friendly.
- Yes
150+ pre-built aggregation functions plus powerful aggregation combinators, fully vectorized and parallelized.
1300+ data processing functions for domains like mathematics, geo, machine learning, time series, and more.
- Yes
Advanced data types like JSON, maps, and arrays plus over 80 array functions for modeling and solving a wide range of problems simply and intuitively.
- Yes
Native support for reading data in over 90 file formats from most data sources which makes it easy to analyze data regardless of its shape and location.
- No
Slower querying speeds and requires more storage.
- No
More costly for BigQuery for analytics workloads.
- No
Support for only standard SQL can make analytics more complex.
- No
Requires writing more complex SQL due to its limited set of aggregate and regular data processing functions.
- No
Support for limited number of data types including only 8 array functions.
- No
Limited interoperability. Supports only 5 file formats and 19 data sources.
Why developers choose ClickHouse
BigQuery’s query latency
BigQuery’s high cost

When not to migrate from BigQuery to ClickHouse Cloud yet?
Both are on our roadmap for 2025.