Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google BigQuery
Score 8.6 out of 10
N/A
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.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Google Sheets
Score 8.5 out of 10
N/A
Google Sheets is the spreadsheet app available on Google Workspace, or standalone, with a free plan for personal use and accessible via mobile apps for iOS and Android.N/A
Pricing
Google BigQueryGoogle Sheets
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Offerings
Pricing Offerings
Google BigQueryGoogle Sheets
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google BigQueryGoogle Sheets
Considered Both Products
Google BigQuery
Chose Google BigQuery
Suits well for Business Intellegence and vizualization with Looker. Cloud storage options and seamless integration with Google online products.
Google Sheets

No answer on this topic

Top Pros
Top Cons
Features
Google BigQueryGoogle Sheets
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.4
51 Ratings
4% below category average
Google Sheets
-
Ratings
Automatic software patching8.117 Ratings00 Ratings
Database scalability8.851 Ratings00 Ratings
Automated backups8.524 Ratings00 Ratings
Database security provisions8.744 Ratings00 Ratings
Monitoring and metrics8.446 Ratings00 Ratings
Automatic host deployment8.113 Ratings00 Ratings
Best Alternatives
Google BigQueryGoogle Sheets
Small Businesses
SingleStore
SingleStore
Score 9.8 out of 10
Microsoft Excel
Microsoft Excel
Score 8.9 out of 10
Medium-sized Companies
SingleStore
SingleStore
Score 9.8 out of 10
Microsoft Excel
Microsoft Excel
Score 8.9 out of 10
Enterprises
SingleStore
SingleStore
Score 9.8 out of 10
Microsoft Excel
Microsoft Excel
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google BigQueryGoogle Sheets
Likelihood to Recommend
8.6
(51 ratings)
8.4
(38 ratings)
Likelihood to Renew
7.0
(1 ratings)
10.0
(1 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
10.0
(9 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
10.0
(1 ratings)
-
(0 ratings)
Professional Services
8.2
(2 ratings)
-
(0 ratings)
User Testimonials
Google BigQueryGoogle Sheets
Likelihood to Recommend
Google
Google BigQuery really shines in scenarios requiring real-time analytics on large data streams and predictive analytics with its machine learning integration. Teams have been using it extensively all over. However, it may not be the best fit for organizations dealing with small datasets because of the higher costs. And also, it might not be the best fit for highly complex data transformations, where simpler or more specialized solutions could be more appropriate.
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Google
Google Sheets is a great tool mostly for people in the finance department such as accountants who have to analyze hundreds of transactions. The software makes it easy to organize data and handle some analysis. Also, when it comes to data presentation, Google Sheets offers some of the best features. However, this is not to sat people outside the finance docket cannot benefit from this software. It is a great tool to have when handling data.
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Pros
Google
  • Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data.
  • Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns.
  • Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds.
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Google
  • It is a cloud-based platform.
  • You can work in the same file simultaneously with your colleagues.
  • It allows you to share files much faster.
  • It allows you to access your Google Sheet files whenever you like and wherever you like if you have stable internet connection.
  • It has great integration with other Google software.
  • Google Sheets is very user-friendly and very intuitive to use.
Read full review
Cons
Google
  • It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses.
  • The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience.
Read full review
Google
  • Pivot tables are different but could be improved upon; sort, totals, filters
  • When entering negative numbers as the first in a formula you need to remember to "+-100+25" instead of "-100+25"
  • The power of the internet of course makes it easy to find solution, but the help function is not easily available
  • Color coding changes on the cell, but there is not an easy way to click on a cell and use the selected color; like excel
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Likelihood to Renew
Google
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
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Google
It is easy to use, free of charge for basic functionality, and easy to share with people within or outside your team or company
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Usability
Google
web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
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Google
No answers on this topic
Support Rating
Google
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
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Google
No answers on this topic
Alternatives Considered
Google
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.
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Google
The major reason I use Google Sheets over Microsoft Excel and Apple Numbers is for its ability to allow multiple users to access and work on the same spreadsheet at once. This is incredibly more efficient and effective than updating and sending copies upon copies of the same Excel or Numbers spreadsheet back and forth as email attachments.
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Contract Terms and Pricing Model
Google
None so far. Very satisfied with the transparency on contract terms and pricing model.
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Google
No answers on this topic
Professional Services
Google
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
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Google
No answers on this topic
Return on Investment
Google
  • Pricing has been very reasonable for us. The first 10 GB of storage is free each month and costs start at 2 cents per GB per month after that. For example, if you store 1 terabyte (TB) for a month, then the cost would be $20. Streaming data inserts start at 1 cent per 200 megabytes (MBs). The first 1 TB of queries is free, with additional analysis at $5 per TB thereafter. Meta data operations are free.
  • Big Query helps reduce the bar for data analytics, ML and AI. BQ takes care of mundane tasks and streamlines for easy data processing, consumption. The most impressive thing is the ML and AI integration as SQL functions, so the need for moving data around is minimized.
  • The visuals of ML models is very helpful to fine tune training, model building and prediction, etc.
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Google
  • We've used it to prepare quick budgets, presentations for funds that have helped raise money
  • It has helped us quickly analyze raw data, collaboratively.
  • it has helped us work more efficiently by making it easier to work from one sheet and not lose track of versions by passing around attached documents
Read full review
ScreenShots

Google BigQuery Screenshots

Screenshot of Migrating data warehouses to BigQuery - Features a streamlined migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the fully managed BigQuery Migration Service.Screenshot of bringing any data into BigQuery - Data files can be uploaded from local sources, Google Drive, or Cloud Storage buckets, using BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, by replicating data from relational databases with Datastream for BigQuery, or by leveraging Google's data integration partnerships.Screenshot of generative AI use cases with BigQuery and Gemini models - Data pipelines that blend structured data, unstructured data and generative AI models together can be built to create a new class of analytical applications. BigQuery integrates with Gemini 1.0 Pro using Vertex AI. The Gemini 1.0 Pro model is designed for higher input/output scale and better result quality across a wide range of tasks like text summarization and sentiment analysis. It can be accessed using simple SQL statements or BigQuery’s embedded DataFrame API from right inside the BigQuery console.Screenshot of insights derived from images, documents, and audio files, combined with structured data - Unstructured data represents a large portion of untapped enterprise data. However, it can be challenging to interpret, making it difficult to extract meaningful insights from it. Leveraging the power of BigLake, users can derive insights from images, documents, and audio files using a broad range of AI models including Vertex AI’s vision, document processing, and speech-to-text APIs, open-source TensorFlow Hub models, or custom models.Screenshot of event-driven analysis - Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows users to make business decisions based on the freshest data. Or Dataflow can be used to enable simplified streaming data pipelines.Screenshot of predicting business outcomes AI/ML - Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets.