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."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"It is a very stable and reliable solution."
"IBM Watson Studio consistently automates across channels."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"The solution is very easy to use."
"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."
"It has a lot of data connectors, which is extremely helpful."
"It is a stable, reliable product."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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."
"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."
"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."
"I think maybe the support is an area where it lacks."
"The main challenge lies in visibility and ease of use."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The solution's interface is very slow at times."
"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 decision making in their decision making feature is less good than other options."
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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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