Google BigQuery

Overview

Reviews

Quit Worrying, Start Using BigQuery

10
Used to deploy this solutioning to the client by shifting away from traditional data warehouse to cloud data warehouse. It resolves the …
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BigQuery = Big Win

9
BigQuery (along with Airflow) has become a critical part of our technology stack. It is being used to support the ingestion of large …
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A Robust Tool for Big Data Analysis

8
Google BigQuery is being used to analyze click-stream data-set in conjunction with structured data-set. It is being used in the sales and …
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BigQuery- A big tool with a lot to offer

7
We use BigQuery to manage large datasets we collect in surveys and in regular work projects. Only one person is in charge of it as we are …
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Google BigQuery: Slow Learning Curve

6
In our organization, Google BigQuery is for storing very large data which is created within seconds. We log each and every event done by …
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Popular Features

View all 6 features

Database scalability (27)

9.9
99%

Automated backups (22)

9.7
97%

Database security provisions (22)

9.7
97%

Monitoring and metrics (23)

8.6
86%

Reviewer Pros & Cons

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Pricing

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Queries (Hourly Flex Slots)

$4

Cloud
per 100 slots

Queries (On-Demand)

$5

Cloud
per TB

Queries (Annual Flat Rate)

$1,700

Cloud
per 100 slots

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

Features Scorecard

Database-as-a-Service

9.6
96%

Product Details

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.

Google BigQuery Technical Details

Deployment TypesSaaS
Operating SystemsUnspecified
Mobile ApplicationNo

Alternatives

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Frequently Asked Questions

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.

What is Google BigQuery's best feature?

Reviewers rate Database scalability highest, with a score of 9.9.

Who uses Google BigQuery?

The most common users of Google BigQuery are from Mid-size Companies and the Computer Software industry.

Reviews

(1-25 of 27)
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Score 10 out of 10
Vetted Review
Verified User
Review Source
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.
Score 9 out of 10
Vetted Review
Verified User
Review Source
As a Data Analyst at my previous company, I dealt primarily with large datasets. Being able to retrieve that data was an important aspect of my job and Google BigQuery made it a lot easier for me. Having worked with the Operations team, I had to use the data in place to find out patterns in them and retrieve a large amount of sales data. At my former organization, BigQuery was used across the organization and it helped a lot to keep all our data at once place with easy access control.
Score 10 out of 10
Vetted Review
Verified User
Review Source
Google Big Query is used by product and services department at my organization. It is used to maintain the various services like bookstore, market place, recreation etc. It is used to maintain the information about inventory, the various vendors and product details. Since it is serverless and can handle large datasets it gives us quick results , work with real time data and helps to handle transactional data.
April 26, 2021

BigQuery = Big Win

Score 9 out of 10
Vetted Review
Verified User
Review Source
BigQuery (along with Airflow) has become a critical part of our technology stack. It is being used to support the ingestion of large amounts of data, manipulating and consolidating that data, and then making it available for other aspects of our technology. The data is at a very large scale and more traditional data stores simply do not have the required performance. For example, some of the same processes if done using a more traditional relational database take hours whereas by utilizing the power of BigQuery take under 1 minute.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Google BigQuery is being used to analyze click-stream data-set in conjunction with structured data-set. It is being used in the sales and marketing departments to essentially attribute new customer acquisition and existing case sales to specific sales representatives, sales divisions, and marketing campaigns. This attribution analysis using Google BigQuery tool has enabled my organization to measure return on investment of various sales and marketing initiatives. Such as training of sales representatives to help their customers adopt digital shopping tools, email, social, and online ordering banner campaigns to target specific customers and regions where we have distribution centers or stores and paid search ads. To accelerate the rate at which we are acquiring new customers who have never shopped before through our online food service business.
Cameron Gable | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
BigQuery is used by our Data Science team to do complex queries on large datasets. We have hundreds of terabytes of data and needed a scalable solution that would be able to query our entire biological dataset. BigQuery plays a crucial role in our data lake made up of several Google Cloud data solutions.
Manjeet Singh | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
It is our main data warehouse. It contains raw data and aggregated data. This is also used for aggregation by running scheduled queries on it. With flat pricing, we are able to optimally use it for aggregation, storage, and exploration. BI tools use BigQuery for data exploration.
Tristan Dobbs | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Reseller
Review Source
Google BigQuery has become our data warehouse for the entirety of the systems that we use. It is incredibly efficient and ridiculously powerful, so it allows us to store all relevant data and query it to build dashboards for management and leadership uses. We connected it directly to a data visualisation tool and it has become the most useful part of our business.
Jose F. Gomez | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Google BigQuery is being used as a data warehousing tool so that we can run analytics and calculate business metrics on our data. It’s very comprehensive and powerful yet provides tools to simplify recurrent queries on the data that makes working with it easy enough. We like that it’s a place where multiple people from interdisciplinary teams can converge on the data and work on finding ways to improve and better understand our business.
Score 10 out of 10
Vetted Review
Verified User
Review Source
Big Query is currently being used by several departments as well as IT to extract data, blend it with other data and to generate reports based on that data. It's being used to track customer journeys through our site, track different channel traffic conversions and to build out dashboards in Tableau.
Sam Lepak | TrustRadius Reviewer
Score 5 out of 10
Vetted Review
Verified User
Review Source
Our marketing team and product development team BigQuery. This is my favorite software for storing information in the cloud, I use it both personally and at work and I recommend it because it has allowed me to access my information very quickly, so far it seems to me that security is very good and not I have had problems with this aspect, although it can work very slow when the Internet connection is not very good, it allows to resume file uploads instead of restarting them every time the signal decreases.
Evan Laird | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use Google BigQuery to mine through further data that Firebase doesn't allow us to. It's been extremely scalable and robust for our SQL and backend developers to mine through and get detailed location data on our users so we can find out where our most active cities are in the United States.
Spencer Baselice | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
BigQuery is in use across the entire organization in various departments and businesses for multiple purposes. It is used to store mass data and analytics from web statistics to business data. It is a data warehouse of sorts where different teams are given access to the platform through a central user management base and each team's sandbox contains relevant data to their function.
Gaurav Gautam | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
BigQuery is a user platform designed to ingest, process and output large volumes of data. We use it to ingest data from Google Analytics and collate that data with other internal data systems by pushing them to BigQuery. BigQuery makes it possible to process a huge volume of data sessions and user levels in almost real-time and achieve personalization and optimized UX.
Anatoly Geyfman | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We use BigQuery as our data warehouse. Meaning, we use BigQuery (BQ) for storing our data, aggregating it and creating pipelines to push data into BQ, and take aggregates out of BQ in order to push them into ElasticSearch. We use it across our whole organization, and most of our data pipelines are now natively using BQ. For us, BQ helped us scale beyond Postgres for very large data sets in a convenient and most importantly, inexpensive way.
Alex Andrews | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Google BigQuery has become the de facto analytics warehouse for our organization. It has allowed us to scale effectively into massive datasets when our internal, physical database could no longer handle these types of workloads. BigQuery is being used by numerous areas within our organization, including my team (Solution Architecture), our internal ETL team, as well as our Advanced Analytics team. BigQuery truly democratizes data access and processing power to anyone that can understand SQL, and has allowed our internal teams to increase the efficiency with which ad hoc analyses can be accomplished on very large datasets.
Score 7 out of 10
Vetted Review
Verified User
Review Source
We use BigQuery to manage large datasets we collect in surveys and in regular work projects. Only one person is in charge of it as we are a small company. It works extremely well for my company because it is cloud-based and we do a lot of remote work, so I can access our data and manage things from anywhere. It's a great tool and makes all kinds of data processing and analysis much easier and faster.
Csaba Toth | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I evaluated and presented introduction to Google BigQuery for the Fresno Google Developer Group technology meetup and also at Google DevFest West conference.
I tried several publicly available datasets, followed several sample queries, studied BigQuery specific instructions. ALso took a look at Google Genomics and its public datasets.
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use BigQuery in our engineering team to do fast analytical queries and generate many reports for the management team. Many of those reports were not possible with our existing data platform because of the time needed to create those reports, and the compute resource required. Google BigQuery solved those problems and enabled our management to access KPI reports in much shorter time.
Reza Qorbani | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We are Big Data company who dealing with petabytes of data and we generate hierarchal data that can be used for Advertising companies. Our customer wanted to query this data via API and extract results where they can have access. Since we are dealing with Terabytes of data to query at any time, we either had option to build 247 infrastructure to support our API requests which would cost us hundreds of thousands of dollar to build, or use BigQuery!

In Our use-case BigQuery not only saved us lots of money but also improve our delivery by almost 100x which was more than what our customers needed. Now our customers can query and extract their data via our API to BigQuery in matter of minutes while previously was in multiple hours!
Score 6 out of 10
Vetted Review
Verified User
Review Source
In our organization, Google BigQuery is for storing very large data which is created within seconds. We log each and every event done by any user. We also log data like payment status, order status, and user address details. Basically, all of the information is logged. To sort through it we are using BigQuery as it is fast and provides data to us within miliseconds.