We performed a comparison between Anaconda and Databricks 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 notebook feature is an improvement over RStudio."
"The virtual environment is very good."
"The most advantageous feature is the logic building."
"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 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 most valuable feature is the set of libraries that are used to support the functionality that we require."
"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."
"It can send out large data amounts."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"There are good features for turning off clusters."
"The technical support is good."
"The solution is very simple and stable."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"It also takes up a lot of space."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"Anaconda should be optimized for RAM consumption."
"When you install Anaconda for the first time, it's really difficult to update it."
"The solution would benefit from offering more automation."
"It would be great if Databricks could integrate all the cloud platforms."
"The Databricks cluster can be improved."
"The initial setup is difficult."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"Can be improved by including drag-and-drop features."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"Anyone who doesn't know SQL may find the product difficult to work with."
Anaconda is ranked 13th in Data Science Platforms with 17 reviews while Databricks is ranked 1st in Data Science Platforms with 78 reviews. Anaconda is rated 8.0, while Databricks 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 Databricks writes "A nice interface with good features for turning off clusters to save on computing". Anaconda is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI, IBM SPSS Statistics and IBM Watson Studio, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio. See our Anaconda vs. Databricks report.
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