Databricks Review

We use this solution for streaming analytics. We use machine learning functions that output to the API and work directly with the database.

Prior to using Azure Databricks in the cloud, we had Databricks installed in clusters. Since our implementation, the performance has increased and our cost has been reduced.

Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great.

This solution has very good machine learning libraries built-in.

The support for big data is good.

Databricks should have more libraries for predictive analysis and machine learning.

It should have more compatible and more advanced visualization and machine learning libraries. As it is now, I have to try a customer algorithm in order for things to be compatible.

I would like to see more deep learning analytics.

I have been using Databricks for about one year.

This is a cluster-based solution, so it is stable.

We started using Databricks with a small PoC application, and then we developed it into a larger one. It's scalable, and it's a simple process to scale.

We have eight people in our team who are using this solution. We do not plan to increase usage at this time.

I did not contact technical support myself, but when one of our team members contacted them they were given good answers. I would say that the support is good.

It is not difficult to deploy this solution because it is well documented. We followed the normal steps that included all of the APIs.

I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.

Databricks has been good and I like it. However, it would be improved with the enhancement of the machine learning libraries, and with the inclusion of visualization libraries.

I would rate this solution an eight out of ten.