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 Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"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 solution is stable."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"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 notebook feature is an improvement over RStudio."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"Easy to use and requires minimal coding and customizations."
"We have the ability to scale, collaborate and do machine learning."
"It's easy to increase performance as required."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"It also takes up a lot of space."
"Anaconda can't handle heavy workloads."
"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 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."
"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 solution would benefit from offering more automation."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"We'd like a more visual dashboard for analysis It needs better UI."
"I would like more integration with SQL for using data in different workspaces."
"Costs can quickly add up if you don't plan for it."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"The integration and query capabilities can be improved."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
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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