We performed a comparison between Amazon SageMaker and Anaconda 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."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."
"We've had no problems with SageMaker's stability."
"The few projects we have done have been promising."
"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"They are doing a good job of evolving."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The notebook feature is an improvement over RStudio."
"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 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."
"I can use Anaconda for non-heavy tasks."
"The virtual environment is very good."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"The solution requires a lot of data to train the model."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"The solution is complex to use."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"Lacking in some machine learning pipelines."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"The solution needs to be cheaper since it now charges per document for extraction."
"It also takes up a lot of space."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"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."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while Anaconda is ranked 13th in Data Science Platforms with 17 reviews. Amazon SageMaker is rated 7.4, while Anaconda is rated 8.0. 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 H2O.ai, whereas Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Microsoft Power BI, IBM SPSS Statistics and IBM Watson Studio. See our Amazon SageMaker vs. Anaconda report.
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