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 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."
"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."
"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."
"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 has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."
"The few projects we have done have been promising."
"The deployment is very good, where you only need to press a few buttons."
"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."
"Voice Configuration and Environmental Management Capabilities are the most valuable features."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"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."
"It helped us find find the optimal area for where our warehouse should be located."
"The most advantageous feature is the logic building."
"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."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"The product must provide better documentation."
"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."
"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."
"SageMaker would be improved with the addition of reporting services."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"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."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"Anaconda should be optimized for RAM consumption."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"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."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
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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