A good big-data powerhouse for analytics and more
March 15, 2024
A good big-data powerhouse for analytics and more
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Google BigQuery
We are using Google BigQuery to store and analyze our big-data and analytics for one of our major projects. We stream different types of data from different sources into BQ and use complex queries to join data from different sources. Data can be queried both programmatically from our application, or displayed using tools like Looker Data Studio.
- Store large amounts of semi-tabular data
- Allows complex and fast queries
- Allows streaming of data from different sources
- Unstructured data is complex to query
- Costs can be high if using large data sets
- It's hard to estimate costs as they depend on usage
- It is easy to use BQ to store large amounts of semi-structured data
- It is to query complex and large data sets
- It is easy to stream data into BigQuery
Compared to SingleStore, BigQuery has a big advantage of being completely serverless, and without practical limitations.
Compared to RedShift, we found the cost model to be more fitted to our needs.
BigQuery also has better integration with Google products, such as Firebase, Google Ads, and Google Analytics, which results in lower TCO for those needs.
Compared to RedShift, we found the cost model to be more fitted to our needs.
BigQuery also has better integration with Google products, such as Firebase, Google Ads, and Google Analytics, which results in lower TCO for those needs.
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