Item: Google BigQuery
Rating: 10
Author: Verified User

Use Cases and Deployment Scope

We use BigQuery to store extremely granular data within our organization. This data is then aggregated to provide very detailed reports to our end users and employees.

Pros and Cons

Reliable
Fast
Extremely powerfull

Need more partitions than just dates
Would like to chose which partition we insert into

Return on Investment

We are able to provide granular reports over trillion of data that we would not be able to provide otherwise

Alternatives Considered

Amazon Redshift, Snowflake and Amazon Athena

We based our analysis primarily on [BigQuery vs. Redshift vs. Athena] and BigQuery proved to be the best solution for us.

Key Insights

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

Other Software Used

Redis, Amazon Elasticsearch Service, Microsoft Visual Studio Code

BigQuery is an extremely powerful tool to store granular data. We have tables with trillions of rows and BigQuery has proven to be extremely reliable over time. For organizations that require a very reliable datastore, BigQuery is an excellent choice. The price is also very reliable given the amount of data we store.

BigQuery is an excellent tool to store and explore granular data

Overall Satisfaction with Google BigQuery