Anaconda vs Google Cloud Datalab comparison

Anaconda and Google are both solutions in the Data Science Platforms category. Anaconda is ranked #11 with an average rating of 8.8, while Google is ranked #15 with an average rating of 7.8. Anaconda holds a 2.1% mindshare in Data Science Platforms, compared to Google’s 1.0% mindshare. Additionally, 95% of Anaconda users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Anaconda and Google Cloud Datalab based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Anaconda vs. Google Cloud Datalab Report (Updated: October 2024).

Buyer's Guide

Anaconda vs. Google Cloud Datalab

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Anaconda is 2.1%, down from 2.3% compared to the previous year. The mindshare of Google Cloud Datalab is 1.0%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Enhancing survey analysis that provides valued insightfulness

I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.

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Rohan Sharma

AI/ML Co-Lead at Developer Student Clubs - GGV

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.

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Nilesh Gode

Project Manager - Data Science at Mettler-Toledo International Inc.

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.

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Quotes from Members

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

Pros

"It is perfectly adequate if all you need are the results and not the trail of evidence."

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."

"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."

"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

More IBM SPSS Statistics pros

"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."

"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 product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."

"It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations."

"Voice Configuration and Environmental Management Capabilities are the most valuable features."

"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."

"I can use Anaconda for non-heavy tasks."

"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."

More Anaconda pros

"All of the features of this product are quite good."

"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."

"For me, it has been a stable product."

"The infrastructure is highly reliable and efficient, contributing to a positive experience."

"Google Cloud Datalab is very customizable."

"The APIs are valuable."

Cons

"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."

"There is a learning curve; it's not very steep, but there is one."

"The solution needs more planning tools and capabilities."

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"Needs more statistical modelling functions."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"It could allow adding color to data models to make them easier to interpret."

More IBM SPSS Statistics cons

"I think that the framework can be improved to make it easier for people to discover and use things on their own."

"Anaconda should be optimized for RAM consumption."

"The solution would benefit from offering more automation."

"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."

"Anaconda can't handle heavy workloads."

"The interface could be improved. Other solutions, like Visual Studio, have much better UI."

"It also takes up a lot of space."

"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."

More Anaconda cons

"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."

"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."

"The product must be made more user-friendly."

"The interface should be 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."

Pricing and Cost Advice

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"More affordable training for new staff members."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"The price of IBM SPSS Statistics could improve."

"I rate the tool's pricing a five out of ten."

"We think that IBM SPSS is expensive for this function."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

More IBM SPSS Statistics pricing and cost advice

"The tool is open-source."

"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."

"The product is open-source and free to use."

"The licensing costs for Anaconda are reasonable."

"My company uses the free version of the tool. There is also a paid version of the tool available."

"The product is cheap."

"It is affordable for us because we have a limited number of users."

"The pricing is quite reasonable, and I would give it a rating of four out of ten."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Computer Software Company

10%

Government

University

Financial Services Firm

20%

Computer Software Company

14%

University

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

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What is your experience regarding pricing and costs for IBM SPSS Statistics?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

See all answers

What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

See all answers

What do you like most about Anaconda?

The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using...

See all answers

What is your experience regarding pricing and costs for Anaconda?

Anaconda does not require a pricing structure, and it is available as an open-source tool. The features of Python, Ju...

See all answers

What needs improvement with Anaconda?

Anaconda consumes a significant amount of processing memory when working on it. This is something that needs improvem...

See all answers

What do you like most about Google Cloud Datalab?

Google Cloud Datalab is very customizable.

See all answers

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...

See all answers

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 serv...

See all answers

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 14% of the time

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

IBM Watson Studio vs IBM SPSS Statistics

Compared 2% of the time

More IBM SPSS Statistics Competitors

Databricks vs Anaconda

Compared 42% of the time

Microsoft Power BI vs Anaconda

Compared 12% of the time

Amazon SageMaker vs Anaconda

Compared 11% of the time

Microsoft Azure Machine Learning Studio vs Anaconda

Compared 10% of the time

Domino Data Science Platform vs Anaconda

Compared 3% of the time

More Anaconda Competitors

Databricks vs Google Cloud Datalab

Compared 25% of the time

Cloudera Data Science Workbench vs Google Cloud Datalab

Compared 19% of the time

IBM SPSS Modeler vs Google Cloud Datalab

Compared 10% of the time

KNIME vs Google Cloud Datalab

Compared 9% of the time

Microsoft Azure Machine Learning Studio vs Google Cloud Datalab

Compared 8% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Anaconda

November 2024

Download Anaconda product report

Buyer's Guide

Google Cloud Datalab

November 2024

Download Google Cloud Datalab product report

Also Known As

SPSS Statistics

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IBM

Anaconda

Google

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone

Information Not Available

Buyer's Guide

Anaconda vs. Google Cloud Datalab

October 2024

Free Report: Anaconda vs. Google Cloud Datalab

Find out what your peers are saying about Anaconda vs. Google Cloud Datalab and other solutions. Updated: October 2024.

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