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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 (50)
    8.8
    88%
  • Database security provisions (43)
    8.7
    87%
  • Automated backups (24)
    8.5
    85%
  • Monitoring and metrics (45)
    8.4
    84%

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

8.4
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 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

(246)

Attribute Ratings

Reviews

(1-25 of 50)
Companies can't remove reviews or game the system. Here's why
Rajender Singh | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery we have used while processing large amount of data when connected with Iot devices in automation factory which continuously give real time data and Google BigQuery can handle it very easily.

Sometime Small volume of data require same effort of writing query which is little bit hectic for users.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
BigQuery has been a great product for getting information from many different sources. We can use BigQuery to connect/join other sources together and find ways to match the data together to have a master data source. There have been times when we have used it, though, when I do not think it was needed and it was probably more of a headache.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Google big query is perfect for simple and fast use-cases where users need to access data quickly and and seamless. GCP IAM makes it easy to have a control on who can access the data and and provides services accounts to automate jobs. Which then makes it easy to have an overview on th data consumption.
Nir Levy | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
I would use Google BigQuery for storing data warehouse information, streaming from multiple sources, and displaying either in my application's dashboard, Looker Studio, or Grafana. It's very easy to stream data from Firebase to BQ, and very effective as well. It is hard to stream data from your main database, and requires some work, but I believe it is worth the effort.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
For organizations looking to avoid the overhead of managing infrastructure, BigQuery's server-less architecture allows teams to focus on analyzing data without worrying about server maintenance or capacity planning. Small projects or startups with limited data analysis needs and tight budgets might find other solutions more cost-effective. Also, it is not suitable for OLTP systems.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Good for large datasets where query performance is otherwise an issue. It is bad for diverse data sources that are not large enough to really benefit and are overkill. Similar to use cases where many users need to query infrequently, where the minor syntax differences between SQL and Google Big Query can be annoying.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery integrated really when with a product that generates enormous amount of data, since appending data to BigQuery is much faster even in high frequency. They also offer a generous free tier which helps in determining its suitability and costs scale according the usage. If you need a really low latency query execution, this might not be what you are looking for.
Score 6 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery handles big data sets really well and has a solid enginge to query and maniulapte the data. The syntax is easy to pick up if your use to other database languages like SQL server but there are some syntax differences. Once setup it is a simple product to use and utilise
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is suited to easily sync/connect different Google products for analytics purposes. Google BigQuery is a great data warehouse if a business use Google Analytics. It also allows more autonomy to various end users with diverse technical knowledge to create dashboards independently in Google Data Studio (now Looker Studio).
Deep Mukherji | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
If you've already invested in the Google Cloud ecosystem and since Google BigQuery is part of the Google Cloud Platform (GCP), it easily integrates with other GCP services like Cloud Storage for data storage and Cloud Data Studio for data visualization. We only pay for the resources we use, unlike traditional data warehouses with fixed costs regardless of usage, thanks to its pay-per-use pricing model with no upfront investment and ongoing maintenance.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is well suited if you have TB or PBs of data which needs to be analyzed with accuracy and then you need to find trends or create dashboards as it has seemless integration with Looker.

Google BigQuery is not well suited if your Database is very small. As the Google BigQuery architecture take similar time in small database which is counter intuitive.
Ilyas Bakirov | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Managed service without any capital investment for users. New users must have knowledge of BigQuery and SQL in order to use it correctly and for its intended purpose. Also scales well and groups according to the size of the dataset and tasks.
Ömer Perçin | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Financial reporting and transactional reporting is suited well for Google BigQuery A lot of data like data streams are supported very well. Small scale usages are not adviced. The integration efforts are not marginal and should not be under estimated Also in case of data security concerns, I think Google is never a best practice to be used provider.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
As previously mentioned Google BigQuery is perfect for storage of you have large data sets since they are charging very minimal charge for storage but they will charge for every single query that you run on Google BigQuery so if you have large data sets then go for it. If you want to do query on the data then Google BigQuery will already provide and you can also build the dashboard with your data on Google Data Studio.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is great when you have a large body of information that needs to be analyzed. It provides an estimate of how much data is going to be queried which can help you identify if you need to optimize your code further before running.
March 12, 2024

Great Data Warehouse.

Score 8 out of 10
Vetted Review
Verified User
Incentivized
BigQuery is great for organizing and preparing data for data analysis, reporting, and visualization. Using Standard SQL to query data within the data warehouse is a comprehensive and resource-rich language that is easy to use and robust. It is very helpful when multiple data sources must be strung together for analysis.
March 12, 2024

Great platform

Score 9 out of 10
Vetted Review
Verified User
Incentivized
I would rate 9 out of 10. The platform's user-friendly interface and ease of learning make it accessible for various team members. Its exceptional capability to handle big data seamlessly aligns with our diverse analytics needs. The serverless architecture streamlines operations, enhancing overall efficiency. While there's room for slight improvements, Google BigQuery remains a valuable asset, significantly impacting our data analytics and decision-making processes.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
- If you are using Google Analytics and there is huge data that is getting streamed every day then you must have Big Query and use it for analysis. It is not only helpful for analysis but also for debugging your Google Analytics implementations.
- For analyzing a small dataset you don't need Big Query you can use normal MySQL on your own premises. Analyzing on Un-structured data is not possible with Big Query.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
I found Google BigQuery very easy to use from the very beginning. Users do need a very good knowledge of SQL in order to write queries that are processed efficiently. Using Select * queries can bog down resources and drive up costs.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Google BigQuery is a great way to manage data across multiple databases within the organisation. The speed of querying makes it highly valuable. The graphs and charts helps analyse the draw insights from the data effectively. We also get a real time understanding of how much time it will take to run the query. We can choose a highly customisable plan as per the need of the organisation to effectively manage the licensing and costs.
Lee L Kennedy | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
If you need a basic data warehouse with some common integrations that are not expensive, Google BigQuery is a good option. If you're a more advanced user looking for more advanced integrations or functionality outside of the normal database/SQL manipulation options that BigQuery has, it might not be suited to your needs.
December 19, 2022

Google BigQuery is ok!

Tia Jones | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Incentivized
In general i think Google BigQuery is good for organizations with large databases and have a need for a cloudless server, I think it is less appropriate when you're looking to do lead scoring or more front end user needs that require machine learning capabilities. It is more for a developer than a marketer, so it was hard to use it for use cases that marketers needed.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
An excellent SQL data management tool without having to manage instances or maintain clusters that need to scale. For a startup or organization that wants to implement a data warehouse logic, it is one of the fastest ways to implement, cheapest to maintain and simple to use that I know of in the market.
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