Running incredibly fast SQL queries using the processing power of Google's infrastructure!
August 26, 2024
Running incredibly fast SQL queries using the processing power of Google's infrastructure!

Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Google BigQuery
I use BQ to get access to the raw data generated from our business mobile app users. It connects to Google Firebase, and then we are enabled to slice and dice the raw data in the BQ environment. Having BQ in place helped us go data-driven without any issues related to the underlying heavyweight tasks of data engineering.
Pros
- Smart and easy query language (GoogleSQL).
- Integration with Looker Studio.
- Creating schedules to run frequent queries.
Cons
- Fonts! are not quite user friendly.
- Integration with other BI tools like Power BI.
- The categorization of Saved Queries, Data Canvases, External Connections, etc., under a certain project makes a long list.
- Increased accessibility to mobile apps data for clickstream analytics.
- Good monitoring that make you on top of the cost and performance.
- No concern about the redundancy and scalability.
When comparing Google BigQuery and Databricks, both platforms are powerful tools for managing and analyzing large datasets. BQ is ideal for businesses requiring large-scale analytics, reporting, and dashboarding with minimal operational overhead. It’s also great for ad-hoc queries on massive datasets without managing the underlying infrastructure. Databricks is best for organizations developing data science and machine learning models, performing complex ETL processes, and handling advanced analytics and AI workflows.
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?
I wasn't involved with the selection/purchase process
Did implementation of Google BigQuery go as expected?
Yes
Would you buy Google BigQuery again?
Yes

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