
What is Google BigQuery?
BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Use BigQuery to manage all data types across clouds, structured and unstructured, with fine-grained access controls. BigQuery's serverless architecture lets you use SQL queries to analyze your data. You can store and analyze your data within BigQuery or use BigQuery to assess your data where it lives.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
88 Likeliness to Recommend
98 Plan to Renew
1
Since last award
87 Satisfaction of Cost Relative to Value
2
Since last award
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+90 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Google BigQuery?
Pros
- Respectful
- Acts with Integrity
- Enables Productivity
- Security Protects
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Data Integration
Data Management
Distributed Processing
Data Security
Analytics and Data Science Tools
Real Time Capabilities
Analytics and Reporting
Workload Management and Monitoring
Platform Administration
Metadata Management
Data Visualization
Vendor Capability Ratings
Business Value Created
Ease of Implementation
Quality of Features
Usability and Intuitiveness
Ease of Data Integration
Vendor Support
Ease of IT Administration
Breadth of Features
Product Strategy and Rate of Improvement
Ease of Customization
Availability and Quality of Training
Google BigQuery Reviews

Derek P.
- Role: Information Technology
- Industry: Insurance
- Involvement: IT Development, Integration, and Administration
Submitted Feb 2023
Gets the job done but could be better.
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
There isn't really anything that differentiates Google BigQuery from others other than maybe SQL syntax-specific quirks. The capabilities and features are on par with others,
What is your favorite aspect of this product?
Since BigQuery's page layout is similar to Redshift and Snowflake, it was an easy transition. In addition, it's very easy to create snapshots. In addition, it's very off-hands, meaning that resources and power can automatically be managed. Also, BigQuery lets you know how expensive a query is prior to running it.
What do you dislike most about this product?
While there isn't anything that I dislike, I think that the platform could do a better job in notifying users of changes that could be made to further optimize our use of BigQuery (whether it's writing queries better, organizing schemas better, and so on).
What recommendations would you give to someone considering this product?
BigQuery gets the job done just like any other competitor like Redshift or Snowflake. However, in rare situations where it matters, most people come from a background having used Redshift or Snowflake only, and therefore, when writing SQL, some things specific to BigQuery might take time getting used to. Other than that, I would take time to architect how you want the infrastructure to look prior to creating. However, if mistakes are made, they are easily correctable.
Pros
- Trustworthy
- Caring
- Respectful
- Client Friendly Policies
Cons
- Less Efficient Service
- Less Effective Service
- Wastes Time
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Elena S.
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Jan 2023
Ideal substitute for conventional data warehouses.
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
The best option, which can save a ton of time, is offered by Google Cloud BigQuery, which also helps with building ML models using only SQL queries. The capability to import data from CSV and other sources is one of its outstanding features. We enjoy working with it.
What is your favorite aspect of this product?
Google Cloud BigQuery is among the most effective options for the data warehouse process. Because it is so easy to use, even a beginner can utilize the device in one sitting. The ability to build ML models using a query is one of its better features and one that I really liked. It makes it very simple to manage large and complex searches.
What do you dislike most about this product?
Bigquery bases its estimation of the cost of a query on the volume of data that has to be processed, hence, it is easy to make costly searches without recognizing it. The number of rows returned by the query will not change, even if I limit it. The new Bigquery SQL editor's autocomplete feature occasionally produces unwanted outcomes.
What recommendations would you give to someone considering this product?
It was first and foremost a fantastic tool that met all of our demands. For our employees, it makes it very easy to manage extensive and complicated searches, and one of its best features, and a feature I particularly like is the capability to build machine learning models using a query. I wish to suggest this to you on their behalf.
Pros
- Helps Innovate
- Performance Enhancing
- Enables Productivity
- Trustworthy
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Austin W.
- Role: Human Resources
- Industry: Technology
- Involvement: End User of Application
Submitted Jan 2023
Less sophisticated yet effective data analysis
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
Google BigQuery is well-liked on the front end because it is cost-effective and easy to use, but when it comes to execution, it is an enterprise data warehouse that is totally serverless, has integrated ML and BI is cross-cloud compatible and expands with all of our business data. We can access and use our data wherever it is by using BigQuery, which eliminates the need for a separate repository to store data.
What is your favorite aspect of this product?
I was able to easily analyze data from the many clouds in a secure, quick, and convenient manner using the Google BigQuery platform, and I was able to disseminate only the outputs that were required and of high quality using a single user interface. With the help of this wonderful technology, we can now dramatically streamline our research, learn new things about spatial data, and build entirely new business potential.
What do you dislike most about this product?
The UI did not particularly appeal to me; in my opinion, it should be more understandable, simple to use, customizable, and logical. Except for it, the query quality is excellent and all other operations go without a hitch. I want to design our dashboards as rapidly as possible based on the needs that are currently a little overwhelming.
What recommendations would you give to someone considering this product?
BigQuery is a tool that can be helpful for massive data as its name implies. Since everything can be done inside the BigQuery Platform with a single touch, using manual ML models is no longer necessary to transform large amounts of raw data into profitable analytics. In contrast to competitors, it provides a less complex yet effective data analysis store that will help business expansion and earnings.
Pros
- Helps Innovate
- Enables Productivity
- Effective Service
- Inspires Innovation
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