We performed a comparison between Databricks and IBM Watson Studio based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Databricks has helped us have a good presence in data."
"The integration with Python and the notebooks really helps."
"The initial setup phase of Databricks was good."
"It is fast, it's scalable, and it does the job it needs to do."
"I work in the data science field and I found Databricks to be very useful."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The simplicity of development is the most valuable feature."
"The initial setup is pretty easy."
"It has a lot of data connectors, which is extremely helpful."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"It has greatly improved the performance because it is standardized across the company."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Watson Studio is very stable."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"Stability-wise, it is a great tool."
"Costs can quickly add up if you don't plan for it."
"I have seen better user interfaces, so that is something that can be improved."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"There is room for improvement in the documentation of processes and how it works."
"Databricks' technical support takes a while to respond and could be improved."
"The integration features could be more interesting, more involved."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"We would like to see it more web-based with more functionality."
"The solution's interface is very slow at times."
"I want IBM's technical support team to provide more specific answers to queries."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The initial setup was complex."
"I think maybe the support is an area where it lacks."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews. Databricks is rated 8.2, while IBM Watson Studio is rated 8.2. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM Watson Studio is most compared with Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI, Amazon Comprehend and IBM SPSS Modeler. See our Databricks vs. IBM Watson Studio report.
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