Analyze Big Data in the cloud with BigQuery. Run fast, SQL-like queries against multi-terabyte datasets in seconds. Scalable and easy to use, BigQuery gives you real-time insights about your data.Try it now
All behind the scenes
Your queries can execute asynchronously in the background, and can be polled for status. Access a history of your jobs and queries alongside the rest of your Cloud Platform resources in the Google Cloud Console.
Import data with ease
Bulk load your data using Google Cloud Storage [link to Cloud Storage page] or stream it in bursts of up to 1,000 rows per second. You can tackle real-time, high-volume logging or transaction recording and have your data available for analysis quickly and easily.
Affordable big data
When we say “Big Data”, we really mean it. The first 100 GB of data processed each month is free. We will store and query thousands of terabytes for you. Our pricing structure is simple and transparent, and we give you full visibility and control. You only pay for the storage you need and the queries you run.
The right interface
Separate interfaces for administration and developers will make sure that you have access to the tools you need. Control access at both the project and dataset level using the Google APIs Console. BigQuery helps teams of any size work the way they want to work.
Learn how the data-crunching capabilities of BigQuery are being put to use by other companies.
"We are always looking for ways to maximize return and minimize investment. BigQuery is the perfect combination. It’s an on-demand, scalable resource."Read Interactions Marketing's story
"We explored several data analytics solutions. Nothing comes remotely close to the sheer power of Google BigQuery. It made large-scale data collection and crunching possible with little effort, which has translated to a significant business advantage."Read redBus's story
BigQuery uses a columnar data structure, which means that for a given query, you are only charged for data processed in each column, not the entire table. The first 100GB of data processed per month is at no charge.
|Storage||$80 (per TB/month)1|
|Interactive queries||$35 (per TB processed)23|
|Batch queries||$20 (per TB processed)2|
2 Charges rounded up to the nearest MB; minimum 1 MB data processed per each table referenced by a query
3 The first 100 GB of data processed per month is at no charge
Package PricingFor increased savings with a committed purchase amount, you can purchase one of the monthly packages described below.These packages apply for interactive queries only. Packages are billed in full at the end of each month, whether the package is used or not. If you use more data than the amount in your chosen package, on-demand rates apply for any additional data. To sign up for a package, contact a sales representative.
|Interactive queries||100 TB||$3,300 per month ($33 per TB processed)|
|400 TB||$12,000 per month ($30 per TB processed)|
|1,500 TB||$40,500 per month ($27 per TB processed)|
|4,000 TB||$100,000 per month ($25 per TB processed)|
Documentation & Resources
Comprehensive documentation and tutorials will teach you how to integrate BigQuery into your application. Learn how to bulk-load data, stream inserts and run queries asynchronously. Access the capabilities of BigQuery from your other Cloud Platform services quickly.
Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google's infrastructure. Simply move your data into BigQuery and let us handle the hard work.
Before you can query your data, you first need to load it into BigQuery. You can bulk load the data by using a job, or stream records individually.
Queries are written in BigQuery's SQL dialect. BigQuery supports both synchronous and asynchronous query methods. Both methods are handled by a job, but the "synchronous" method exposes a timeout value that waits until the job has finished before returning.