Make predictive analytics accessible
Build, test, and operationalize custom ML models using familiar SQL and greatly simplify the model-building process with automated feature engineering, model selection, and hypertuning steps. Store trained models inside BigQuery and share easily with stakeholders for seamless collaboration.
Accelerate time to insights
Build ML models in minutes instead of days or weeks directly inside BigQuery without the need to extensively sample the data or move it out of the data warehouse for training. Optionally, BigQuery ML can automatically update the trained ML models based on changes in the underlying data, saving time from manually retraining models.
Scale without compromise
Use the power of BigQuery’s serverless architecture and the power of Google Cloud to train ML models on petabyte-scale data in minutes — a fraction of the time compared to conventional systems. Enable data analysts and citizen data scientists in your organization to easily collaborate and build ML solutions. BigQuery ML empowers you to build mission-critical predictive analytics solutions without compromise.
- Serverless data warehousing gives you the resources you need, when you need them. With BigQuery, you can focus on your data and analysis, rather than operating and sizing computing resources.
- Real-time Analytics
- BigQuery’s high-speed streaming insertion API provides a powerful foundation for real-time analytics. BigQuery allows you to analyze what’s happening now by making your latest business data immediately available for analysis.
- Automatic High Availability
- Free data and compute replication in multiple locations means your data is available for query even in the case of extreme failure modes. BigQuery transparently and automatically provides durable, replicated storage and high availability with no extra charge and no additional setup.
- Standard SQL
- BigQuery supports a standard SQL dialect which is ANSI:2011 compliant, reducing the need for code rewrite and allowing you to take advantage of advanced SQL features. BigQuery provides free ODBC and JDBC drivers to ensure your current applications can interact with BigQuery’s powerful engine.
- Federated Query and Logical Data Warehousing
- BigQuery breaks down data silos so you can analyze all your data assets from one place. Through powerful federated query, BigQuery can process data in object storage (Cloud Storage), transactional databases (Cloud Bigtable), or spreadsheets in Google Drive — all without duplicating data. One tool lets you query all your data sources.
- Storage and Compute Separation
- BigQuery provides you with fine-grained control of cost and access. With BigQuery’s separated storage and compute, you pay only for the resources you use. You have the option to choose the storage and processing solutions that make sense for your business and control access for each.
- Automatic Backup and Easy Restore
- BigQuery automatically replicates data and keeps a seven-day history of changes, reducing worries about unexpected data changes. This allows you to easily restore and compare data from different times.
- Geospatial Datatypes and Functions
- BigQuery GISALPHA brings SQL support for the most commonly used GIS functions right into your data warehouse. With support for arbitrary points, lines, polygons, and multi-polygons in WKT and GeoJSON format, you can simplify your geospatial analyses, see your location-based data in new ways, or unlock entirely new lines of business with the power of BigQuery. Request early access to BigQuery GISALPHA here.
- Data Transfer Service
- BigQuery makes it easy to get started with data warehousing, even if your data is in a SaaS application. The BigQuery Data Transfer Service automatically transfers data from external data sources, like Google Marketing Platform, Google Ads, and YouTube, to BigQuery on a scheduled and fully managed basis.
- Big Data Ecosystem Integration
- With Cloud Dataproc and Cloud Dataflow, BigQuery provides integration with the Apache Big Data ecosystem, allowing existing Hadoop/Spark and Beam workloads to read or write data directly from BigQuery. BigQuery allows you to get the most out of structured data by making it easy to analyze in SQL and easy to integrate with your existing Big Data jobs, so you don’t have to throw away the work you’ve already done.
- Petabyte Scale
- BigQuery is fast and easy to use on data of any size. With BigQuery, you’ll get great performance on your data, while knowing you can scale seamlessly to store and analyze petabytes more without having to buy more capacity.
- Flexible Pricing Models
- BigQuery enables you to choose the pricing model that best suits you. On-demand pricing lets you pay only for the storage and compute that you use. Flat-rate pricing enables high-volume users or enterprises to choose a stable monthly cost for analysis. For more information see BigQuery pricing.
- Data Encryption and Security
- You have full control over who has access to the data stored in BigQuery. BigQuery makes it easy to maintain strong security with fine-grained identity and access management with Cloud Identity and Access Management, and your data is always encrypted at rest and in transit.
- Data Locality
- You have the option to store your BigQuery data in US, Japan, and European locations while continuing to benefit from a fully managed service. BigQuery gives you the option of geographic data control, without the headaches of setting up and managing clusters and other computing resources in-region.
- Foundation for AI
- BigQuery provides a flexible, powerful foundation for machine learning and artificial intelligence. Besides bringing ML to your data with BigQuery ML, integrations with Cloud ML Engine and TensorFlow enable you to train powerful models on structured data. Moreover, BigQuery’s ability to transform and analyze data helps you get your data in shape for machine learning.
- Foundation for BI
- BigQuery forms the data warehousing backbone for modern BI solutions, and enables seamless data integration, transformation, analysis, visualization, and reporting with tools from Google and our technology partners.
- Flexible Data Ingestion
- Load your data from Cloud Storage or Cloud Datastore or stream it into BigQuery at thousands of rows per second to enable real-time analysis of your data. Use familiar data integration tools like Informatica, Talend, and others out of the box.
- Data Governance
- BigQuery provides fine-grained access controls on data and role-based control on API through integration with Cloud IAM. With BigQuery and Cloud IAM, you can be sure your data is safe from unauthorized access.
- Programmatic Interaction
- BigQuery provides a REST API for easy programmatic access and application integration. To enable programmers of all types, BigQuery offers client libraries in Java, Python, Node.js, C#, Go, Ruby, and PHP. Business users can use Google Apps Script to access BigQuery from Google Sheets.
- Rich Monitoring and Logging with Stackdriver
- BigQuery provides rich monitoring, logging, and alerting through Stackdriver Audit Logs. BigQuery resources can be monitored at a glance, and BigQuery can serve as a repository for logs from any application or service using Stackdriver Logging.
- Cost Controls
- BigQuery provides cost control mechanisms that enable you to cap your daily costs. See more information on cost controls.
BigQuery Solutions and Use Cases
|Storage||$0.02 per GB, per month
$0.01 per GB, per month for long-term storage
|Streaming Inserts||$0.01 per 200 MB|
|Loading, Copying, or Exporting Data;
When querying data, you can choose from two different pricing options:
|Pay-as-you-go||$5 per TB
First terabyte (1 TB) per month is free*
|Flat-rate pricing||Starting at $40,000/month for a dedicated reservation of 2,000 slots.
For more information, see flat-rate pricing.
|Subscription Type||Machine Learning Models||Price|
|$5 per GB of training data, per model created**
First 10 GB of training data per month is free
$5 per TB of data, for prediction/evaluation queries
|Model creation and prediction consumes current slots, as normal, through July 31, 2019|
See additional details for BigQuery ML pricingIf you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.