We performed a comparison between Amazon SageMaker and Anaconda based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."
"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"We've had no problems with SageMaker's stability."
"They are doing a good job of evolving."
"We were able to use the product to automate processes."
"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."
"The notebook feature is an improvement over RStudio."
"The virtual environment is very good."
"With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."
"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 Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."
"The solution requires a lot of data to train the model."
"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"The solution is complex to use."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"SageMaker would be improved with the addition of reporting services."
"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."
"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while Anaconda is ranked 13th in Data Science Platforms with 15 reviews. Amazon SageMaker is rated 7.4, while Anaconda is rated 7.8. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". On the other hand, the top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and SAS Visual Analytics, whereas Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Microsoft Power BI, IBM SPSS Statistics and IBM Watson Studio.
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