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 documentation is excellent and the solution has a very large and active community that supports it."
"It helped us find find the optimal area for where our warehouse should be located."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"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 virtual environment is very good."
"The most advantageous feature is the logic building."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"Ability to work collaboratively without having to worry about the infrastructure."
"The solution is an impressive tool for data migration and integration."
"Databricks helps crunch petabytes of data in a very short period of time."
"The ability to stream data and the windowing feature are valuable."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"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 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."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"When you install Anaconda for the first time, it's really difficult to update it."
"Anaconda can't handle heavy workloads."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"It also takes up a lot of space."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"There are no direct connectors — they are very limited."
"Costs can quickly add up if you don't plan for it."
"There is room for improvement in the documentation of processes and how it works."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The integration features could be more interesting, more involved."
"Anyone who doesn't know SQL may find the product difficult to work with."
"Pricing is one of the things that could be improved."
"Doesn't provide a lot of credits or trial options."
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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