ClickHouse vs BigQuery: Using ClickHouse to Serve Real-Time Queries on Top of BigQuery Data

Google BigQuery and ClickHouse are complementary technologies that can be used together for real-time analytics. ClickHouse excels at delivering sub-second performance on predictable query access patterns, while BigQuery is optimized for ad-hoc querying with low QPS scenarios. To synchronize data between BigQuery and ClickHouse, users can deploy ClickHouse alongside BigQuery to speed up queries or use scheduled queries, Google DataFlow, or manual exports/import operations. ClickHouse storage efficiency is better than BigQuery's, achieving 8x compression, but requires more granular precision in data types and schemas. The authors provide a step-by-step guide on how to load Ethereum blockchain data into ClickHouse from BigQuery, including bulk loading, incremental loading, and handling failures, as well as examples of optimized queries that can be executed on top of the loaded data.

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