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."We were able to use the product to automate processes."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"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."
"Allows you to create API endpoints."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"The deployment is very good, where you only need to press a few buttons."
"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."
"The documentation is excellent and the solution has a very large and active community that supports it."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."
"The virtual environment is very good."
"It helped us find find the optimal area for where our warehouse should be located."
"The notebook feature is an improvement over RStudio."
"The solution is stable."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."
"There are other better solutions for large data, such as Databricks."
"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."
"AI is a new area and AWS needs to have an internship training program available."
"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."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"Lacking in some machine learning pipelines."
"The documentation must be made clearer and more user-friendly."
"When you install Anaconda for the first time, it's really difficult to update it."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"The solution would benefit from offering more automation."
"One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known."
"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."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"Anaconda can't handle heavy workloads."
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 Dataiku, 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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