Overall Satisfaction with Google BigQuery
We use BigQuery in our engineering team to do fast analytical queries and generate many reports for the management team. Many of those reports were not possible with our existing data platform because of the time needed to create those reports, and the compute resource required. Google BigQuery solved those problems and enabled our management to access KPI reports in much shorter time.
- It's capable of scanning billions of records in a couple of seconds. It makes it possible to create hundreds of KPIs in less than an hour.
- Google BigQuery provides the compute power when you need it. For a startup company, BlueCava cannot afford the massive compute power required for the reports we'd like to create, and BigQuery makes this available.
- The best part, Google BigQuery is charged per query, and based on the size of data the query scans. No extra cost.
- Documentation is not complete, sometimes not clear.
- Performance is unstable occasionally.
- Error message not clear.
- Increased employee efficiency: interactive analytical queries can run much faster on BigQuery, problems are discovered/identified quicker.
- KPI reports are delivered to management much quicker.
- Overall reduced cost for BlueCava.
Comparing to competitors, Google BigQuery has the lowest cost and most flexible pricing model. Definitely higher ROI.
It is well suited for generating reports quickly or doing interactive analytical queries over a large data set that contains hundreds of millions or billions of rows. The largest table we used in BigQuery has close to 30 billion rows. It is not suited for ETC processes or data pipeline.