We use BigQuery as a data source.
We mainly use it to do some transformations. Once we collect query data from it, we use other services to do model training or predictions. We don't really utilize all the features provided by BigQuery. We mainly use some basic data transformation options. It also provides some machine learning models.
In many functions, it's very similar to Spark Kubernetes. The cluster is good. It'll provide computation capabilities.
The setup is simple.
It is stable. The performance is good.
It is a scalable solution.
We do not find the solution that expensive.
Machine learning could be improved. There are some machine learning models in BigQuery; however, maybe more libraries can be provided. We'd like it extended into the Spark ML library.
I noticed recently it's more expensive now. I didn't compare them to others, however, and in our team, we don't consider the price of it much.
I've been using the solution for several months.
It is stable and reliable. There are no bugs or glitches.
I'd rate the overall stability an eight out of ten. It offers a good level of performance. There are billions of accounts.
It's scalable. We don't need to worry about scalability issues in our case. For us, it's good enough.
We have millions of customers and thousands of products.
I've never dealt with technical support. I can't speak to how helpful or responsive they are. We have a bigger team and tend to learn from each other.
I also use Spark, which has similar functions. I've also used Databricks.
I've used BigQuery for a longer time, however, Databricks is easier when it comes to the setup of a complete solution. With BigQuery, we need to develop an intranet solution and set up services and then put them together.
It is my understanding that the initial setup is very straightforward and simple.
The pricing is fine.
I'd rate the solution seven out of ten. It's a pretty good product overall.
