We performed a comparison between DataRobot and IBM Watson Studio based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."DataRobot can be easy to use."
"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."
"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."
"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."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"Stability-wise, it is a great tool."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It has greatly improved the performance because it is standardized across the company."
"IBM Watson Studio consistently automates across channels."
"Watson Studio is very stable."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."
"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."
"The initial setup was complex."
"The main challenge lies in visibility and ease of use."
"I want IBM's technical support team to provide more specific answers to queries."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"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."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"The decision making in their decision making feature is less good than other options."
"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."
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DataRobot is ranked 13th in AI Development Platforms with 3 reviews while IBM Watson Studio is ranked 8th in AI Development Platforms with 13 reviews. DataRobot is rated 8.6, while IBM Watson Studio is rated 8.2. The top reviewer of DataRobot writes "Easy to manage jobs and see the logs if there's any drift in a model, user-friendly, and the data munching is fast". 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". DataRobot is most compared with Amazon SageMaker, RapidMiner, Microsoft Azure Machine Learning Studio, Datadog and Alteryx, whereas IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and Amazon Comprehend. See our DataRobot vs. IBM Watson Studio report.
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