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 solution is stable."
"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."
"It helped us find find the optimal area for where our warehouse should be located."
"The notebook feature is an improvement over RStudio."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"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 documentation is excellent and the solution has a very large and active community that supports it."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"Google Cloud Datalab is very customizable."
"All of the features of this product are quite good."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"The solution would benefit from offering more automation."
"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 interface could be improved. Other solutions, like Visual Studio, have much better UI."
"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."
"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."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while Google Cloud Datalab is ranked 15th 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, KNIME and Qlik Sense.
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