We performed a comparison between Anaconda and IBM Watson Studio based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The solution is stable."
"The notebook feature is an improvement over RStudio."
"The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."
"The virtual environment is very good."
"The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"It helped us find find the optimal area for where our warehouse should be located."
"It has greatly improved the performance because it is standardized across the company."
"The solution is very easy to use."
"It is a very stable and reliable solution."
"The system's ability to take a look at data, segment it and then use that data very differently."
"The scalability of IBM Watson Studio is great."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"It is a stable, reliable product."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"Anaconda can't handle heavy workloads."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"When you install Anaconda for the first time, it's really difficult to update it."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"The solution would benefit from offering more automation."
"The main challenge lies in visibility and ease of use."
"We would like to see it more web-based with more functionality."
"I want IBM's technical support team to provide more specific answers to queries."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"The initial setup was complex."
"So a better user interface could be very helpful"
"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."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews. Anaconda is rated 7.8, while IBM Watson Studio is rated 8.2. The top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". 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". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and RapidMiner, whereas IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and SAS Visual Analytics.
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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
