We performed a comparison between Anaconda and Oracle Essbase based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The most advantageous feature is the logic building."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"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."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"The solution is stable."
"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."
"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."
"The solution can handle a large volume of data."
"The solution is scalable."
"Unlike relational, where you're linking together multiple tables, with Essbase, you basically define what the dimensions are beforehand, and you define the hierarchy, and then load the data. This allows you to do a pretty sophisticated analysis so that you can drill into it and slice and dice the data."
"It is highly efficient and easily scalable, particularly for handling large databases."
"It helps us fetch specific data sets per users' requirements."
"The solution is stable and reliable."
"Essbase is extremely stable and low-maintenance."
"I have found the most valuable aspect is the user-friendly environment and current features."
"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."
"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."
"The solution would benefit from offering more automation."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"Anaconda should be optimized for RAM consumption."
"They should improve the solution's performance."
"Essbase has a programming language, and it has a couple of functions to do forecasting, however, their feature set for that is not that good."
"I would like to see an integration with application performance management and a version control management tool."
"The ability to drive external reporting out for development could be improved."
"There is room for improvement in terms of cost-effectiveness."
"It's an expensive product to use."
"The initial setup is pretty complex."
"The initial setup could be simplified."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while Oracle Essbase is ranked 10th in Database Development and Management with 10 reviews. Anaconda is rated 7.8, while Oracle Essbase is rated 8.4. 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 Oracle Essbase writes "It is easy to use and receives patch updates on regular intervals ". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and IBM SPSS Statistics, whereas Oracle Essbase is most compared with Microsoft Power BI, SAP BusinessObjects Business Intelligence Platform, SAP Analytics Cloud, Oracle Analytics Cloud and Tableau.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
