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."I haven't heard about any major stability issues. At this time I feel like it's stable."
"It is a cost-effective solution."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"The solution is very easy to use."
"The setup is quite easy."
"It's easy to increase performance as required."
"Its lightweight and fast processing are valuable."
"IBM Watson Studio consistently automates across channels."
"It has a lot of data connectors, which is extremely helpful."
"It is a stable, reliable product."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Watson Studio is very stable."
"Stability-wise, it is a great tool."
"It is a very stable and reliable solution."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"Costs can quickly add up if you don't plan for it."
"Would be helpful to have additional licensing options."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"The product cannot be integrated with a popular coding IDE."
"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."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"The main challenge lies in visibility and ease of use."
"The decision making in their decision making feature is less good than other options."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"I want IBM's technical support team to provide more specific answers to queries."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"Some of the solutions are really good solutions but they can be a little too costly for many."
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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