Google

Google BigQuery

Composite Score

8.8 /10

CX Score

9.1 /10

76 Reviews Write a Review

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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.

Company Details

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Awards & Recognition

Google BigQuery won the following awards in the Analytical Data Store category

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2024 Emotional Footprint Champion

Latest Award, 2024

Service Experience
Contract Negotiation

Latest Award, 2024

2024 Data Quadrant Gold Medalist

2024

8 Top Rated Capabilities

4 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Service Experience
Contract Negotiation
Conflict Resolution

2023

2023 Data Quadrant Gold Medalist

2023

8 Top Rated Capabilities

6 Top Rated Features

2023

2022 Emotional Footprint Champion

2022

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2022

2022 Data Quadrant Gold Medalist

2022

10 Top Rated Capabilities

5 Top Rated Features

2022

2021 Emotional Footprint Champion

2021

Google BigQuery Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Google BigQuery.

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.

87 Likeliness to Recommend

96 Plan to Renew

90 Satisfaction of Cost Relative to Value

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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?

3% Negative

3% Neutral

94% Positive

Pros

Respectful
Acts with Integrity
Caring
Security Protects

Feature Ratings

Average 84

Data Management

Data Integration

Distributed Processing

Real Time Capabilities

Analytics and Data Science Tools

Metadata Management

Data Security

Platform Administration

Analytics and Reporting

Workload Management and Monitoring

Data Visualization

Vendor Capability Ratings

Average 84

Business Value Created

Ease of IT Administration

Vendor Support

Ease of Implementation

Usability and Intuitiveness

Quality of Features

Ease of Data Integration

Breadth of Features

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of Customization

Google BigQuery Reviews

Role: Information Technology
Industry: Engineering
Involvement: Business Leader or Manager

Validated Review

Anonymous Reviewer

Submitted Jul 2024

It is very easy to use , and cost friendly

Likeliness to Recommend

10 /10

Pros

Helps Innovate
Continually Improving Product
Reliable
Trustworthy

Srikanth C.

Role: Information Technology
Industry: Engineering
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Jul 2024

Easy Data Querying with Big Query

Likeliness to Recommend

9 /10

What differentiates Google BigQuery from other similar products?

Since Big Query lies within Googles Cloud Platform it gets very convenient to process data in GCP and store it in Big Query to easily Query stored data. This is not the case with other open source services as data ingestion and management gets difficult.

What is your favorite aspect of this product?

Using Google Big Query we could easily make a upper Cap on the spend for the processing we use. The data here is also safely replicated and provide options like snapshots to retain data prior updating. The Storage configurations are simple and the queries can be ran on schedule without manual interference.

What do you dislike most about this product?

Permissions related to the dataset are a little difficult to configure. Also it is a bit hard to integrate with other cloud services relational data.

What recommendations would you give to someone considering this product?

A Basic understanding of Google Clod platform and structured SQL data bases is recommended.

Pros

Unique Features
Efficient Service
Effective Service
Over Delivered

Matthias S.

Role: Information Technology
Industry: Consulting
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jun 2024

Process and analyze meaningful data sets.

Likeliness to Recommend

9 /10

What differentiates Google BigQuery from other similar products?

It is very scalable and can handle massive data sets quickly and efficiently, among other things.

What is your favorite aspect of this product?

I love its intuitive and friendly interface because it makes it easy to load data, execute SQL queries, and view results.

What do you dislike most about this product?

Dislike The expenses associated with using Google BigQuery can be a limitation.

What recommendations would you give to someone considering this product?

I highly recommend it thanks to its distributed architecture and parallel processing capabilities; It also has exceptional query execution performance. Even with huge data sets, this allows real-time analysis results.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Google BigQuery

What is Google BigQuery?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

2024 Data Quadrant Gold Medalist

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

2022 Emotional Footprint Champion

2022 Data Quadrant Gold Medalist

2021 Emotional Footprint Champion

Google BigQuery Ratings

87 Likeliness to Recommend

96 Plan to Renew

90 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+90 Net Emotional Footprint

How much do users love Google BigQuery?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Management Includes data sharing, data storage, records management, and data security.

Data Integration Includes integration of data from multiple sources, merging systems, transforming data and capture data to form a unified view of a company's data assets

Distributed Processing Data storage and processing is shared among many physical or virtual independents servers or sites for high volume data with seamless access to large datasets.

Real Time Capabilities Ability to analytics and visualize data as soon as it becomes available in underline systems.

Analytics and Data Science Tools Includes Analytics and Data science components such as AI, statistical and machine learning libraries

Metadata Management Easily manage metadata associated with customer data or audience segments.

Data Security Includes ability to hide sensitive data by masking with special characters or anonymous information.

Platform Administration Includes back-end interface and administrative capabilities

Analytics and Reporting Includes historical & real-time dashboard visualizations, detailed & summary reporting and easy data extraction for data analysis.

Workload Management and Monitoring Includes task, performance, monitoring and time management

Data Visualization Thematic visualization with the ability to change views, including color, pattern/icon, dot-density, chart, scaled-symbol, and 3D prism themes

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Google BigQuery Reviews

It is very easy to use , and cost friendly

Likeliness to Recommend

Pros

Srikanth C.

Easy Data Querying with Big Query

Likeliness to Recommend

Pros

Matthias S.

Process and analyze meaningful data sets.

Likeliness to Recommend

Pros

Most Popular Google BigQuery Comparisons

Amazon Redshift

Snowflake

Microsoft Azure Synapse Analytics

Cloudera Data Platform

SAP HANA Cloud

Oracle Exadata

Feature Ratings

Data Management

Data Integration

Distributed Processing

Real Time Capabilities

Analytics and Data Science Tools

Metadata Management

Data Security

Platform Administration

Analytics and Reporting

Workload Management and Monitoring

Data Visualization

Vendor Capability Ratings

Business Value Created

Ease of IT Administration

Vendor Support

Ease of Implementation

Usability and Intuitiveness

Quality of Features

Ease of Data Integration

Breadth of Features

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of Customization