Skip to main content
TrustRadius
Google BigQuery

Google BigQuery

Overview

What is Google BigQuery?

Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

Read more
Recent Reviews
Read all reviews

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 6 features
  • Database scalability (51)
    8.8
    88%
  • Database security provisions (44)
    8.8
    88%
  • Automated backups (24)
    8.5
    85%
  • Monitoring and metrics (46)
    8.5
    85%

Reviewer Pros & Cons

View all pros & cons
Return to navigation

Pricing

View all pricing

Standard edition

$0.04 / slot hour

Cloud

Enterprise edition

$0.06 / slot hour

Cloud

Enterprise Plus edition

$0.10 / slot hour

Cloud

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://cloud.google.com/bigquery/prici…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
Return to navigation

Product Demos

Lesson#6 - BigQuery for beginners| Analyzing data in google bigquery | Step by step tutorial (2020)

YouTube

How to get started with BigQuery

YouTube

BigQuery, IPython, Pandas and R for data science, starring Pearson

YouTube

Google BigQuery Demo

YouTube

Google BigQuery introduction by Jordan Tigani

YouTube
Return to navigation

Features

Database-as-a-Service

Database as a Service (DBaaS) software, sometimes referred to as cloud database software, is the delivery of database services ocer the Internet as a service

8.5
Avg 8.7
Return to navigation

Product Details

What is Google BigQuery?

Google BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data. At the core of Google’s data cloud, BigQuery can be used to simplify data integration and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make an organization’s operations more data-driven.

Google BigQuery Features

Database-as-a-Service Features

  • Supported: Database scalability
  • Supported: Database security provisions
  • Supported: Monitoring and metrics

Additional Features

  • Supported: Unified experience for all analytics users
  • Supported: Duet AI in BigQuery
  • Supported: Flexibility, predictable pricing, and best price performance
  • Supported: Built-in machine learning
  • Supported: Analyze and share data across clouds
  • Supported: Real-time analytics with streaming data pipelines
  • Supported: Unify, manage, and govern all types of data
  • Supported: Share insights with built-in business intelligence
  • Supported: Geospatial analysis with BigQuery
  • Supported: Real-time change data capture and replication

Google BigQuery Competitors

Google BigQuery Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

Google BigQuery starts at $0.

Snowflake and Amazon Redshift are common alternatives for Google BigQuery.

Reviewers rate Database scalability and Database security provisions highest, with a score of 8.8.

The most common users of Google BigQuery are from Enterprises (1,001+ employees).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(248)

Attribute Ratings

Reviews

(1-2 of 2)
Companies can't remove reviews or game the system. Here's why
Richard Atkins | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Data warehousing. Streaming and batch ingest of files and APIs. Implementing business logic, combining data from different sources, reformatting, reporting, and optimization automation
  • Standard SQL
  • Scale
  • RDBMS-like features
  • Python library support
  • Reliability
  • Python library authentication simplification
  • multi-transaction ACID compliance
Well; data warehousing transformation flexible ingestion
Database-as-a-Service (6)
78.33333333333333%
7.8
Automatic software patching
100%
10.0
Database scalability
100%
10.0
Automated backups
100%
10.0
Database security provisions
90%
9.0
Monitoring and metrics
80%
8.0
Automatic host deployment
N/A
N/A
  • Reduced time to market of features compared to legacy warehouse
  • Improved engineer productivity
  • Simplified TCO
  • Improved data security
The web UI, general features, libraries, and integration with other products is continuously improving and already very strong
web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
Requests and escalation are often quickly acted, however usually done through specific individuals instead of teams, therefore continuity may not always be smooth.
50
20
Score 10 out of 10
Vetted Review
Verified User
Used to deploy this solutioning to the client by shifting away from traditional data warehouse to cloud data warehouse. It resolves the issue of transparency in terms of payment per month, utilization and on how to allow user level access to different folders. It also allows for full integration with other Google Cloud Platform's components like Compute Engine and PubSub.
  • Transparency in terms of cost
  • Utilisation of the data warehouse and suggestion on the sizes
  • Easy to use and integration with other components
  • UiUX features can be improved further in terms of navigating from one folder to another
I would say that Google BigQuery are well suited for all scenarios, be it small scale projects or big projects where you have to maintain a huge chunk of data, you will find good budget to go with it. Easy to use for someone who is not well versed with cloud platform too.
Database-as-a-Service (6)
98.33333333333334%
9.8
Automatic software patching
100%
10.0
Database scalability
100%
10.0
Automated backups
90%
9.0
Database security provisions
100%
10.0
Monitoring and metrics
100%
10.0
Automatic host deployment
100%
10.0
  • Reduced time to integrate from one components to another
  • Reduced the cost for cloud warehousing
  • Ease of use so reduced time to get to use on a daily basis
Google Support members are very helpful in resolving the issues and queries. Any questions or queries will be entertained at a timely manner with professionalism, as well as tips and improvement that can be done for the proposed solutioning. In the case that some functionalities are not present within Google BigQuery, they are more than happy to admit the limitation and would like feedback for improvement.
Easy to use and to integrate. In terms of scalability, the size of the BigQuery can easily scale to suit the need of the process and design. No glaring limitation in terms of use for Google BigQuery based on the use for 1 year, and will continue to feel so after many years due to the support.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
None so far. Very satisfied with the transparency on contract terms and pricing model.
Return to navigation