We receive an ROI for our batch constructs. 

We see an ROI from Databricks. 

We have seen a return on investments.

We have seen a return on our investment with Databricks.

It's a good return on investment for Databricks from a delivery perspective. Delivered multiple dashboards. So, it's quite a good return on investment. And being a small organization, everyone can use Databricks, and cost-wise, it's also good for small organizations.

We've had a low ROI from Databricks.

On a scale from one to five, I would give our ROI a three.

It's too soon to tell what kind of return we're getting because we just started using it, and we're still migrating.

We have seen an ROI but cannot differentiate because it also comes with the Azure platform.

We have seen a return on investment.

I have seen an ROI using Databricks.

Our ROI was of the order of USD $75k per year for one deployment. We were able to switch our workloads from an onsite Hadoop cluster, billed to our department for more than USD $100k per year, to a Databricks workspace in the cloud for a quarter of that expenditure. 

Further, we were able to transparently and efficiently scale our queries to run under fifteen minutes per major analytics use case, while being subject to unstable queries and highly brittle data flow use cases from the in-house Hadoop cluster.

We are further reducing spending on our traditional RDBMS solution by offloading reporting workloads to the Databricks PySpark notebooks, which is reducing our expensive datacenter resources and freeing up RDBMS resources for OLTP loads. 

I would say the ROI for this solution is expressed mainly in terms of effort and time.

Don't really know.