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 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."
"Voice Configuration and Environmental Management Capabilities are the most valuable features."
"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 documentation is excellent and the solution has a very large and active community that supports it."
"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."
"The most advantageous feature is the logic building."
"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's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"It's great technology."
"Automation with Databricks is very easy when using the API."
"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"The technical support is good."
"I like cloud scalability and data access for any type of user."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"It also takes up a lot of space."
"When you install Anaconda for the first time, it's really difficult to update it."
"The solution would benefit from offering more automation."
"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."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"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 should be optimized for RAM consumption."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"The pricing of Databricks could be cheaper."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"There should be better integration with other platforms."
"We'd like a more visual dashboard for analysis It needs better UI."
"I would like it if Databricks made it easier to set up a project."
"It would be great if Databricks could integrate all the cloud platforms."
"The tool should improve its integration with other products."
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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