Anaconda vs Dataiku comparison

Anaconda and Dataiku are both solutions in the Data Science Platforms category. Anaconda is ranked #11 with an average rating of 8.8, while Dataiku is ranked #7 with an average rating of 7.5. Anaconda holds a 2.1% mindshare in Data Science Platforms, compared to Dataiku’s 11.5% mindshare. Additionally, 95% of Anaconda users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

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Executive Summary

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

Buyer's Guide

Anaconda vs. Dataiku

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 Dataiku is 11.5%, up from 7.5% 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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Sabrine Bendimerad

Data Scientist at Electricite De France

Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

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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 has the ability to easily change any variable in our research."

"The most valuable feature is the user interface because you don't need to write code."

"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."

"in terms of the simplicity, I think the SPSS basic can handle it."

"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."

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

"IBM SPSS Statistics depends on AI."

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

More IBM SPSS Statistics pros

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

"It helped us find find the optimal area for where our warehouse should be located."

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

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

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

"The most advantageous feature is the logic building."

"The solution is stable."

"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."

More Anaconda pros

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

"The solution is quite stable."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"Data Science Studio's data science model is very useful."

"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

"The most valuable feature is the set of visual data preparation tools."

"Cloud-based process run helps in not keeping the systems on while processes are running."

More Dataiku pros

Cons

"Needs more statistical modelling functions."

"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."

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

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

"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."

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

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."

More IBM SPSS Statistics cons

"It also takes up a lot of space."

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

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

"When you install Anaconda for the first time, it's really difficult to update it."

"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."

"Anaconda consumes a significant amount of processing memory when working on it."

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

More Anaconda cons

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"The ability to have charts right from the explorer would be an improvement."

"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."

"I think it would help if Data Science Studio added some more features and improved the data model."

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."

"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."

More Dataiku cons

Pricing and Cost Advice

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

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

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

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

"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 affordable training for new staff members."

"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 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."

"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 licensing costs for Anaconda are reasonable."

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."

"Pricing is pretty steep. Dataiku is also not that cheap."

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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

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

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...

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 is your experience regarding pricing and costs for Dataiku Data Science Studio?

It is very expensive.

See all answers

What needs improvement with Dataiku Data Science Studio?

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...

See all answers

What is your primary use case for Dataiku Data Science Studio?

We use the solution for data science and machine learning.

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 Dataiku

Compared 38% of the time

KNIME vs Dataiku

Compared 15% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

More Dataiku 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

Dataiku

November 2024

Download Dataiku product report

Also Known As

SPSS Statistics

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Dataiku DSS

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IBM

Anaconda

Dataiku

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

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

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

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

Buyer's Guide

Anaconda vs. Dataiku

October 2024

Free Report: Anaconda vs. Dataiku

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

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