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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The virtual environment is very good."
"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."
"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 product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"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."
"I can use Anaconda for non-heavy tasks."
"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."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"The solution is very easy to use."
"It is a cost-effective solution."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"The most valuable feature is the ability to use SQL directly with Databricks."
"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."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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."
"Anaconda can't handle heavy workloads."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"Anaconda should be optimized for RAM consumption."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"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."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"Would be helpful to have additional licensing options."
"I would like more integration with SQL for using data in different workspaces."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"I have seen better user interfaces, so that is something that can be improved."
"The integration of data could be a bit better."
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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