Introduction to BigQuery BI Engine

Introduction

BigQuery BI Engine is a fast, in-memory analysis service. By using BI Engine you can analyze data stored in BigQuery with sub-second query response time and with high concurrency.

BI Engine integrates with familiar Google tools like Google Data Studio to accelerate data exploration and analysis. With BI Engine, you can build rich, interactive dashboards and reports in Data Studio without compromising performance, scale, security, or data freshness.

Advantages of BI Engine

BI Engine has the following advantages:

  • Fast: Match performance to the speed of business by reducing time to insights
    Today, it's difficult to run reports fast enough to steer your business in a data-driven way by using operational, prescriptive business intelligence. Teams also struggle with sluggish dashboards and stale data. BI Engine provides sub-second query response time with minimal load times and improved concurrency for data stored in BigQuery. By integrating BI Engine with BigQuery streaming, you can perform real-time data analysis over streaming data without sacrificing write speeds or data freshness.
  • Simplified architecture: Get started quickly without managing complex data pipeline or servers
    Traditional BI systems requires users to move data from data warehousing platforms to data marts or BI platforms to support fast interactive analysis. This typically requires complex ETL pipelines for data movement. The time required by these ETL jobs can delay your reporting and compromise the freshness of data for critical decision support systems. BI Engine performs in-place analysis within BigQuery. This eliminates the need to move data or to create complex data transformation pipelines.
  • Smart tuning: Very few configuration settings
    BI Engine's self-tuning design automatically tunes queries by moving data between BI Engine's in-memory storage, the BigQuery query cache, and BigQuery storage to ensure optimal performance and load times for dashboards. Your BigQuery administrator can easily add and remove BI Engine memory capacity by using the BigQuery UI in the GCP Console.

Supported regions

Like BigQuery, BI Engine is a multi-regional resource. During the beta period, BI Engine supports the following locations.

Regional locations

Region Name Region Description
Americas
us-west2 Los Angeles
northamerica-northeast1 Montréal
us-east4 Northern Virginia
southamerica-east1 São Paulo
Europe
europe-north1 Finland
europe-west2 London
europe-west6 Zürich
Asia Pacific
asia-east2 Hong Kong
asia-south1 Mumbai
asia-east1 Taiwan
asia-northeast1 Tokyo
asia-southeast1 Singapore
australia-southeast1 Sydney

Multi-regional locations

Multi-Region Name Multi-Region Description
EU European Union
US United States

BI Engine processes queries in the same location as the dataset that contains the tables you're querying. For more information, see Dataset locations in the BigQuery documentation.

Limitations

BI Engine is subject to the following limitations during the beta period:

  • BI Engine is currently only available for use with Data Studio.
  • Queries against BigQuery views are not fully optimized by BI Engine.
  • The maximum amount of data that you can have cached in BI Engine memory is 10 GB.
  • Data Studio custom queries are not fully optimized by BI Engine.

Pricing

For information on BI Engine pricing, see the Pricing page.

Quotas

For information on BI Engine quotas, see the Quotas and limits page.

What's next

  • Get started with BI Engine using Google Data Studio.
  • Learn how to reserve BI Engine capacity.
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