Databricks Review

Easy to switch loads between clusters and automation is easy using the API


What is our primary use case?

I am a developer and I do a lot of consulting using Databricks.

We have been primarily using this solution for ETL purposes. We also do some migration of on-premises data to the cloud.

What is most valuable?

The most valuable feature is the ability to switch loads between multiple clusters.

Automation with Databricks is very easy when using the API.

The ability to write code and SQL in the same interface is useful.

It is easy to connect notebooks to a cluster.

There are a large number of inbuilt functions that help to make things easier.

What needs improvement?

Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems. As it is now, we have to go into the driver logs to identify the error messages properly. 

There is not much information about Databricks available online, such as cost. Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful.

I would like to see integration with Power BI or Tableau for the business users. They may use Databricks to check on things, but it will be a little bit complicated for them. The GUI interfaces for Tableau and Power BI are ones that they are used to, so the integration would help.

For how long have I used the solution?

I have been using Databricks for about five and a half years.

What do I think about the stability of the solution?

We have found that in the development environment, Databricks is pretty stable. We have had problems where something works in development but does not work in production, and this can happen when the version is updated and certain features have been deprecated. This means that more testing is required before moving to production, but this is the only drawback that we have seen.

Basically, when we move across version we have found issues, but otherwise, it's pretty stable.

What do I think about the scalability of the solution?

Scalability is one of the main features of Databricks. We have used datasets that are one hundred megabytes in size up to one terabyte, and we can manage, so it's easily scalable.

We have a large company with between 400 and 500 people using this solution.

How are customer service and technical support?

We have not reached out for technical support on Databricks.

How was the initial setup?

I found the initial setup easy because I had previously worked on Spark.

If somebody goes through the training, which is available on the website, then it should be straightforward. I don't think that it is very hard.

When it comes to developing things based on use cases, it can take between three days and two weeks, plus two to three days for testing and deploying it. I would say that for an entire use case, it will take a maximum of three weeks.

What other advice do I have?

My advice for developers who are interested in working with this solution is to first go through the Spark architecture.

I would rate this solution a nine out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)

Disclosure: I am a real user, and this review is based on my own experience and opinions.

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