Anaconda vs Darwin comparison

Anaconda and SparkCognition are both solutions in the Data Science Platforms category. Anaconda is ranked #11 with an average rating of 8.8, while SparkCognition is ranked #27. Anaconda holds a 2.1% mindshare in Data Science Platforms, compared to SparkCognition’s 0.3% mindshare. Additionally, 95% of Anaconda users are willing to recommend the solution, compared to 100% of SparkCognition users who would recommend it.

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Executive Summary

We performed a comparison between Anaconda and Darwin 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. Darwin Report (Updated: October 2024).

Buyer's Guide

Anaconda vs. Darwin

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 Darwin is 0.3%, up from 0.3% 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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AaronCooke

Founder at Helio Summit

Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.

There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.

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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

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

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"Most of the product features are good but I particularly like the linear regression analysis."

"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."

"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

"One feature I found very valuable was the analysis of variance (ANOVA)."

"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."

"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."

More IBM SPSS Statistics pros

"The most valuable feature is the set of libraries that are used to support the functionality that we require."

"The most advantageous feature is the logic building."

"The virtual environment is very good."

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

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

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

"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 solution is stable."

More Anaconda pros

"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."

"I liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable."

"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."

"The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate."

"In terms of streamlining a lot of the low-level data science work, it does a few things there."

"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."

"The thing that I find most valuable is the ability to clean the data."

"Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision."

Cons

"The product should provide more ways to import data and export results that are user-friendly for high-level executives."

"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

"Better documentation on how to use macros."

"This solution is not suitable for use with Big Data."

"It could provide even more in the way of automation as there are many opportunities."

"Technical support needs some improvement, as they do not respond as quickly as we would like."

"The statistics should be more self-explanatory with detailed automated reports."

More IBM SPSS Statistics cons

"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."

"It also takes up a lot of space."

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

"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."

"Anaconda can't handle heavy workloads."

"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."

"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 should be optimized for RAM consumption."

More Anaconda cons

"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."

"Our main data repository is on AWS. The trouble we are having is that we have to download the data from our repository to bring it into Darwin. It would be great if there was an API to connect our repository to Darwin."

"There are issues around the ethics of artificial intelligence and machine learning. You need to have a lot of transparency regarding what is going on under the hood in order to trust it. Because so much is done under the hood of Darwin, it is hard to trust how it gets the answers it gets."

"The challenge is very big toward making models operational or to industrialize them. E.g., what we want to do is to make unique credit models for each customer. So, we are preparing the types of customers who we can try new credit models on Darwin. But, I see this still very challenging to be able to get the data sets so Darwin can work. At this point, we are working it to get the data sets ready for Darwin."

"Something they are working on, which is great, is to have an API that can access data directly from the source. Currently, we have to create a specific dataset for each model."

"An area where Darwin might be a little weak is its automatic assessment of the quality of datasets. The first results it produces in this area are good, but in our experience, we have found that extra analysis is needed to produce an extra-clean set of data."

"The analyze function takes a lot of time."

"The Read Me's and the tutorials need to be greatly improved to get customers to understand how things work. It might be helpful to have some sample data sets for people to play around with, as well as some tutorial videos. It was very hard to find information on this in the time crunch that we had, to see how it worked and then make it work, while interfacing with folks at SparkCognition."

Pricing and Cost Advice

"The price of this solution is a little bit high, which was a problem for my company."

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

"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."

"The price of IBM SPSS Statistics could improve."

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

"It's quite expensive, but they do a special deal for universities."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

More IBM SPSS Statistics pricing and cost advice

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

"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 tool is open-source."

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

"The license cost is not cheap, especially not for markets like Mexico. But sometimes, you do have to make these leap of faith for some tools to see if they can get you the disruption that you are aiming for. The investment has paid off for us very well."

"In just six months, we calculated six million pesos that we have prevented in revenue from going away with another customer because of this solution. Thanks to Darwin, we didn't lose those six million pesos."

"As far as I understand, my company is not paying anything to use the product."

"I believe our cost is $1,000 per month."

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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

Computer Software Company

25%

Real Estate/Law Firm

13%

Government

13%

Educational Organization

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

See all answers

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...

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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...

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What do you like most about Anaconda?

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

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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

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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

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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

IBM Watson Studio vs Darwin

Compared 100% of the time

More Darwin 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

Darwin

November 2024

Download Darwin product report

Also Known As

SPSS Statistics

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IBM

Anaconda

SparkCognition

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

SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.

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

Hunt Oil, Hitachi High-Tech Solutions

Buyer's Guide

Anaconda vs. Darwin

October 2024

Free Report: Anaconda vs. Darwin

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