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. The BI Engine SQL interface feature also integrates with other popular business intelligence (BI) tools, such as Looker, Tableau, Power BI, and custom applications to accelerate data exploration and analysis.
With BI Engine, you can build rich, interactive dashboards and reports 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 Cloud Console.
Using BI Engine with Data Studio has the following limitations:
- Some types of queries against BigQuery views are not fully optimized by BI Engine. When a query is not optimized, Data Studio displays a detailed reason.
- Each BI Engine project per location can cache a maximum of 100 GB in memory.
- BI Engine for Data Studio supports a maximum of 500 partitions per table.
- BI Engine for Data Studio supports up to 150 million rows of queried data, depending on query complexity.
For a list of limitations to BI Engine query acceleration, including BigQuery API and other BI tools, see BigQuery BI Engine SQL interface overview.
For a full list of optimized functions and operators in custom queries and views, see Optimized SQL functions and operators.
BI Engine is supported in the same regions as BigQuery. See the Locations page for a complete list of supported regions and multi-regions.
For information on BI Engine pricing, see the BI Engine Pricing page.
For information on BI Engine quotas, see the Quotas and limits page.
- Get started with BI Engine using Google Data Studio.
- Learn about using BI Engine with other business intelligence tools.
- Learn how to reserve capacity.