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Anaconda vs Google Cloud Datalab comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Anaconda
Ranking in Data Science Platforms
11th
Average Rating
8.2
Reviews Sentiment
7.4
Number of Reviews
19
Ranking in other categories
No ranking in other categories
Google Cloud Datalab
Ranking in Data Science Platforms
16th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (19th)
 

Mindshare comparison

As of July 2025, in the Data Science Platforms category, the mindshare of Anaconda is 2.1%, up from 2.1% compared to the previous year. The mindshare of Google Cloud Datalab is 1.0%, down from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Rohan Sharma - PeerSpot reviewer
Provides all the frameworks and makes it easy to create environments for multiple projects
The best thing is that it provides all the frameworks and makes it easy to create environments for multiple projects using Anaconda. It is easy for a beginner to learn to use Anaconda. Comparatively, it is easier than using virtual environments or other environments because of the Conda environment. However, there are many things in Anaconda that people need to be aware of, so it can be challenging.
Nilesh Gode - PeerSpot reviewer
Easy to setup, stable and easy to design data pipelines
The scalability is average. We have not faced any issues with scalability. There are more than 500 end users using this solution in our company. It is an integral part of the daily operations. The usage pattern is not a one-time thing; employees regularly access and utilize the application. We use it at a global level with a scattered user base. This means that users don't all use the application at the same time. So, around 300 out of 500 employees use the solution, and this usage is spread out throughout the day.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations."
"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 most advantageous feature is the logic building."
"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."
"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."
"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."
"Google Cloud Datalab is very customizable."
"For me, it has been a stable product."
"All of the features of this product are quite good."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
 

Cons

"It also takes up a lot of space."
"The solution would benefit from offering more automation."
"Anaconda consumes a significant amount of processing memory when working on it."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"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."
"The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools."
"When you install Anaconda for the first time, it's really difficult to update it."
"The product must be made more user-friendly."
"The interface should be more user-friendly."
"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."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"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."
 

Pricing and Cost Advice

"The product is open-source and free to use."
"My company uses the free version of the tool. There is also a paid version of the tool available."
"The licensing costs for Anaconda are reasonable."
"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"The tool is open-source."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"The product is cheap."
"It is affordable for us because we have a limited number of users."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
9%
Manufacturing Company
8%
Government
7%
Financial Services Firm
23%
University
12%
Computer Software Company
9%
Manufacturing Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Anaconda?
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.
What is your experience regarding pricing and costs for Anaconda?
Anaconda is an open-source tool, so I do not pay anything for it. It is compatible with every tool, regardless of whether it is open source or a paid package.
What needs improvement with Anaconda?
There is room for improvement, especially regarding deployment. The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools.
What do you like most about Google Cloud Datalab?
Google Cloud Datalab is very customizable.
What needs improvement with Google Cloud Datalab?
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcin...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Information Not Available
Find out what your peers are saying about Anaconda vs. Google Cloud Datalab and other solutions. Updated: June 2025.
860,592 professionals have used our research since 2012.