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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.

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Recent Reviews
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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

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Pricing

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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
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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
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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
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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).
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Comparisons

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Reviews and Ratings

(249)

Attribute Ratings

Reviews

(1-25 of 40)
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Rajender Singh | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
The data performance of Google BigQuery is best as per other software. Limitations on Google BigQuery's data size are superior to those of Microsoft SQL. Obtaining real-time data from several IoT devices is another benefit.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I personally find it by far simpler than Amazon Redshift due it's onboarding seamlessness. For a quick start and simplify tye access to read the data big query provide better user experience and a smoother user interface. More importantly, the fact that Big Query can be easily integrated with Looker Studio for visualisations. Query data and visualizing has never been easier.
Nir Levy | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Compared to SingleStore, BigQuery has a big advantage of being completely serverless, and without practical limitations.

Compared to RedShift, we found the cost model to be more fitted to our needs.

BigQuery also has better integration with Google products, such as Firebase, Google Ads, and Google Analytics, which results in lower TCO for those needs.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
BigQuery can automatically scale to accommodate the data and query load, providing potentially unlimited scalability. At the same time, Redshift requires manual scaling efforts to increase or decrease capacity, which might affect performance during scaling operations.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We focused more on data volume and less on full application capabilities. All in all, we found that the two solutions complement each other. For integration, some sources were better handled in SAP HANA, particularly other SAP systems where Google Big Query was more suitable for various R&D data, such as time series.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is the best among the ones we evaluated. It works really well with the Google Cloud workloads and comes with exceptional security controls. It can be combined easily with lots of products that Google Cloud has. It is a real game-changer.
Score 6 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery i would say is better to use than AWS Redshift but not SQL products but this could be due to being more experience in Microsoft and AWS products. It would be really nice if it could use standard SQL server coding rather than having to learn another dialect of SQL server. It was choosen due to the 3rd parties choice of software.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
The principal advantage against them and the reason we chose Google BigQuery is the pay-as-you-go service. Every company wants to reduce costs. With this flexible model based on usage, we reduced at least half of the amount we were paying with Azure. Google BigQuery overpasses them because they don't offer that flexible model for companies.
Deep Mukherji | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
First and foremost, Google BigQuery's pricing structure, based on data processing and storage, is more cost-effective for our needs. Secondly, since we already use other Google Cloud services, its tight integration with them especially, with Cloud Storage and Dataflow was a big plus and streamlined data transfer and simplified our workflows. Apart from that, as my team deals with large datasets and complex queries, we need a serverless architecture technology that has an edge in terms of query speed and scalability for our specific needs.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery seemlessly integrates with all the Google services. In Looker Studio you directly have a connector for Google BigQuery which can help to create dashboards in few clicks.
For automating some stored procedures we have used Cloud Functions which are triggered by a PubSub topic when an event happens.
Ömer Perçin | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is a fully managed, serverless data warehouse offered by Google Cloud Platform. It stands out for its scalability, performance, and ease of use compared to other data warehouse solutions. Here's how it stacks up against others. Google BigQuery is designed to handle massive datasets, allowing you to store and query petabytes of data without worrying about infrastructure management or performance degradation.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Cost is the important factor for us compared with all of the other tools Google BigQuery stands top among all of them which charges very minimal charges for storage against all the apps that we have liked the most additionally, we can do query on our data, and can build dashboard on Google data Studio so we that's why we have preferred Google BigQuery against all of the other apps.
March 12, 2024

Great Data Warehouse.

Score 8 out of 10
Vetted Review
Verified User
Incentivized
I was already familiar with the Google Cloud Platform environment, and I was better equipped with the standard SQL language. Some of the syntax does not translate well to Redshift. It also seemed like many data source integrations relevant to our business were easier and more readily available for BigQuery versus Redshift.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is less expensive to run and offers free storage of up to the first 10 GB of data. Google BigQuery is also easier (and faster) to get up and running. Unlike Snowflake, Google BigQuery does not require any manual scaling or performance tuning. Scaling is completely automatic.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery manages data like no one else. The light speed of running queries makes it a one stop solution. The editor and query builder also have a highly intuitive interface that makes it easy to build new queries fast. Google BigQuery can easily be integrated with other google products like gmail and drive allowing the team to get real time updates and actionables.
December 19, 2022

Google BigQuery is ok!

Tia Jones | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Treasure Data is more for the marketer rather than a developer audience, so depending on who your main users will be for the machine learning you can decide which tool is better. In our case we went with Treasure Data because it was more for a marketer and less for the developer side.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
BigQuery has a simpler and more intuitive user experience (as is the case with most of its products) compared to AWS, which has a more technical and complex profile, so it was the first tool we used. It's still my go-to option for handling SQL queries, though it doesn't detract from Athenas if the rest of the infrastructure is on AWS.
Score 10 out of 10
Vetted Review
Verified User
At my previous organization we used server based SQL server. There were days when the server was down and we couldn't work or access the data. This caused multiple reports and processes which were fed from the server to fail. Google BigQuery doesn't have such problems.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
I have used Snowflake and DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. For example, the reliability of Google is unmatchable by others. One thing that I really like is the ability to integrate Data Studio so easily with Google BigQuery.
April 26, 2021

BigQuery = Big Win

Score 9 out of 10
Vetted Review
Verified User
Incentivized
We selected BigQuery since we were already making use of many other offerings within the Google Cloud Platform and it made sense to stay within that eco-system. Of course, we made sure it met our needs and was cost-effective, and when it did we didn't seriously consider an alternative from another vendor.
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