Your company ingests terabytes of semi-structured web clickstream data every day. Analysts want to issue interactive SQL queries across the entire dataset without having to provision or tune any database servers. Which Google Cloud product is the most appropriate choice?
BigQuery is a fully managed, serverless data warehouse that automatically scales to petabyte volumes and lets users analyze data with standard SQL. It requires no infrastructure management and is optimized for ad-hoc analytics.
Cloud Bigtable is a NoSQL wide-column store intended for low-latency key/value access, not SQL analytics.
Cloud Spanner is a globally distributed relational database optimized for transactional consistency, not large-scale analytical workloads.
Cloud SQL provides managed MySQL, PostgreSQL, and SQL Server instances but requires capacity planning and is not designed for petabyte-scale analytics.
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What is serverless computing in the context of BigQuery?
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What is BigQuery and why is it suitable for analyzing large datasets?
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How does BigQuery differ from Cloud Bigtable when analyzing data?
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Why is Cloud Spanner not suited for analyzing petabyte-scale datasets?
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