We performed a comparison between Anaconda and Google Cloud Datalab based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"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 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 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 documentation is excellent and the solution has a very large and active community that supports it."
"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."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"The solution would benefit from offering more automation."
"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."
"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 could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"Anaconda can't handle heavy workloads."
"The interface should be more user-friendly."
"The product must be made more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while Google Cloud Datalab is ranked 14th in Data Science Platforms with 5 reviews. Anaconda is rated 7.8, while Google Cloud Datalab is rated 7.6. 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 Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and IBM SPSS Statistics, whereas Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, IBM SPSS Modeler and KNIME.
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