Google BigQuery Studio's Pros & Cons
Updated April 16, 2025

Google BigQuery Studio's Pros & Cons

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Google BigQuery

Google BigQuery is very powerful tool for Processing & Retrieving the data. millions of records you can retrieve & fetch, do the joins operations and all in just seconds. As our company is having data in millions of records so to perform retrieval, update, delete & process operations. It also provides pay as you go service. So, it is great tool to save time as well as cost. We can also run AI/ML Models directly in Google BigQuery studio no need to build the models explicitly. UI is very easy to understand even non-techie's also understood it easily.

Pros

  • Very fast processing & Computation power is very good.
  • Scheduling queries & Creating Views is super easy.
  • AI/ML Models can be created in Google BigQuery studio itself, no need to build models explicitly.
  • UI is very good, even non-technical persons can understand it easily.
  • Well organized

Cons

  • Even if you have saved views name in your dataset and if you refresh the page because of network issues or any other issues it wont show your views names instead it'll show untitled query in studio. Then again you have go to your view path and have to open and edit it from your left side panel.
  • If we are working on small project then it is fine But when we're working on big projects where we have to open 10-15 views and edit it then that time it'll be hectic.
  • If I want to schedule query/view all days of the month except 1-2 days then I cant schedule it like that.
  • e.g. In one of my projects I had to schedule the view for all days in a month except 1st of each month so that I was unable to do.
  • Gemini AI Query Recommendations can be improved
  • ROI is pretty good on Google BigQuery. They will help you understand all the aspects & features of the products and where we can use which features. Also they'll help you and your team by providing training regarding the same if required.
  • You can provide row-level access to all the users and can authorize whom to give which access. Also monitor their activity and usage to get the insights if any sudden increase in cost for any month or week.
  • Our organization is having last 5-6 years of data so to save that much history data we had to spend more but Google BigQuery providing the solution where we can store our frequent usable data in standard storages and history data can be stored in cold storages with very minimal cost.

Do you think Google BigQuery delivers good value for the price?

Yes

Are you happy with Google BigQuery's feature set?

Yes

Did Google BigQuery live up to sales and marketing promises?

Yes

Did implementation of Google BigQuery go as expected?

Yes

Would you buy Google BigQuery again?

Yes

If you want to save time as well as cost then go for Google BigQuery studio in terms of Computation & Processing speed.
If your client/vendors uploading your transactional data in GCS buckets then for transformations we have fetch that data to Google BigQuery studio then we have to write DAGs for it even if you have to fetch 1 single file still the process is same. There they can do some improvements if number of files we have to fetch from buckets to studio is less or one time only with lesser size.

Google BigQuery Feature Ratings

Database-as-a-Service
8.0
Database scalability
8
Database security provisions
8
Monitoring and metrics
8

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