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Google BigQuery
A fast, economical, and fully managed data warehouse for
large-scale data analytics
Features & Benefits
Fully managed by Google:
• Google seamlessly deploys, maintains, and upgrades
your database, Google is on-call to monitor uptime, and
Google knows if your jobs fail - when they fail.
Easy to use:
• Just upload your data and run SQL.
• No cluster deployment, no virtual machines, no setting
keys or indexes, and no software.
Multitenancy built-in:
• No need to deploy multiple clusters and duplicate data
into each one. Manage permissions on projects and
datasets with Access Control Lists.
Seamlessly scales with usage:
• Storage and Compute are separate.
• Storage scales to Petabytes.
• Compute scales with usage without cluster resizing.
• Use thousands of cores per query.
• Only pay for what you use, not what you deploy.
Highly available and durable out-of-the-box
• Deployed across multiple data centers by default, with
multiple factors of replication to optimize maximum
data durability and service uptime.
Incredibly fast:
• Analyze terabytes of data in seconds.
• Stream millions of rows per second for
real-time analysis.
The Google pedigree:
• Powered by Dremel, Google’s internal analytics suite.
• In production at Google since 2008.
• BigQuery in production since 2012.
• BigQuery and Dremel process exabytes of data
every month.
BigQuery top use cases:
• Gaming telemetry
• Retail and e-commerce
• loT
• Log analytics
To get started with BigQuery:
Go to cloud.google.com/BigQuery
The first 1TB of data processed
per month is free
1 2
3 4
5 6
7
25.5s elapsed, 3.70 TB processed

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Google BigQuery - Features & Benefits

  • 1. Google BigQuery A fast, economical, and fully managed data warehouse for large-scale data analytics Features & Benefits Fully managed by Google: • Google seamlessly deploys, maintains, and upgrades your database, Google is on-call to monitor uptime, and Google knows if your jobs fail - when they fail. Easy to use: • Just upload your data and run SQL. • No cluster deployment, no virtual machines, no setting keys or indexes, and no software. Multitenancy built-in: • No need to deploy multiple clusters and duplicate data into each one. Manage permissions on projects and datasets with Access Control Lists. Seamlessly scales with usage: • Storage and Compute are separate. • Storage scales to Petabytes. • Compute scales with usage without cluster resizing. • Use thousands of cores per query. • Only pay for what you use, not what you deploy. Highly available and durable out-of-the-box • Deployed across multiple data centers by default, with multiple factors of replication to optimize maximum data durability and service uptime. Incredibly fast: • Analyze terabytes of data in seconds. • Stream millions of rows per second for real-time analysis. The Google pedigree: • Powered by Dremel, Google’s internal analytics suite. • In production at Google since 2008. • BigQuery in production since 2012. • BigQuery and Dremel process exabytes of data every month. BigQuery top use cases: • Gaming telemetry • Retail and e-commerce • loT • Log analytics To get started with BigQuery: Go to cloud.google.com/BigQuery The first 1TB of data processed per month is free 1 2 3 4 5 6 7 25.5s elapsed, 3.70 TB processed