We performed a comparison between Anaconda and SAP Analytics Cloud based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."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 product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"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 is stable."
"I can use Anaconda for non-heavy tasks."
"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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The documentation is excellent and the solution has a very large and active community that supports it."
"We mainly use Analytics Cloud because it integrates with other SAP solutions. Our ERP is an SAP product, and our back-end is SAP Business Warehouse, so integration is an essential factor."
"The most useful feature of SAP Analytics Cloud is planning because it helps users with making predictions and forecasts. Clients can forecast, make data allocations, and other actions. The solution is useful for planning."
"Technical support is helpful."
"Visualization is quite seamless and awesome. Once the data messaging is set up, it's straightforward and simple to select how it should be displayed. So, that's another advantage of SAP."
"The user interface is quite good for developing reports out of models."
"It is a comprehensive BI solution that provides reporting, planning, and predictive analytics in one solution. You don't have to buy three different products. It is very flexible. It can be implemented very quickly. It has a lot of out-of-the-box scenarios that you can use for quick deployment."
"The solution is quite effective for collaborative planning."
"I like the predictive features of SAP. It's easy to use tools for an end-user."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"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."
"The solution would benefit from offering more automation."
"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."
"Anaconda can't handle heavy workloads."
"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 business intelligence features should be improved because there is a lack of functionality regarding that part."
"Pricing is fine for the BI license, but when it comes to client license, that fee is a bit high."
"The price, integration, and modeling capabilities could be better. I have to use an integration engine to integrate our products and databases. SAP Analytics Cloud is made specifically for KPIs and business intelligence. The modeling capabilities are kind of poor. You always have to model the data and then present it visually in SAP Analytics Cloud. In the next release, I would like to have a lite version for planning to create scenarios quickly. For me personally, planning is the most complicated feature of SAP Analytics Cloud."
"It should have the flexibility for scoping the story and models. When you use it in a three-layer architecture, you struggle with the fact that you usually have just one SAP Analytics Cloud tenant, and you have to switch the connections, which might be an issue for bigger developments. For the development role, there should be an option to switch between development and production scenarios."
"They need a better scalability rate."
"Its integration or connectivity with non-SAP systems, big data, and social media, such as YouTube, LinkedIn, et cetera, can be improved. This is where SAP has limited features as compared to other solutions."
"What should be improved in SAP Analytics Cloud is the speed of importing information and data, e.g. from SAP S/4HANA. Gathering the data from the main database takes a bit of time."
"It's lacking a bit in maturity and we find we can't run our business off it until it's improved."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while SAP Analytics Cloud is ranked 4th in BI (Business Intelligence) Tools with 58 reviews. Anaconda is rated 7.8, while SAP Analytics Cloud is rated 8.0. 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 SAP Analytics Cloud writes "Good for reporting but needs to improve its predictive analytics features". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and SAP BusinessObjects Business Intelligence Platform, whereas SAP Analytics Cloud is most compared with SAP BusinessObjects Business Intelligence Platform, Tableau, IBM Planning Analytics, Microsoft Power BI and Anaplan.
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.
