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.

Comparison Buyer's Guide

Download the report

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

Download the complete report

Helped 814,649 peers since 2012

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

Sep 21, 2023

Enhancing survey analysis that provides valued insightfulness

I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…

Read full review

Rohan Sharma

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

May 9, 2024

Provides all the frameworks and makes it easy to create environments for multiple projects

I have been very enthusiastic about artificial intelligence and machine learning since my first year. I started learning Python in my first year and was using a MacBook with the M1 chip, which didn't have native Python support. I discovered Anaconda, which developed Python for Mac, so I started…

Read full review

Sabrine Bendimerad

Data Scientist at Electricite De France

Jun 11, 2024

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.

Read full review

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 feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

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

"It offers very good visualization."

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

"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."

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

"SPSS is quite robust and quicker in terms of providing you the output."

More IBM SPSS Statistics pros

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

"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."

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

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

"The notebook feature is an improvement over RStudio."

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

"The solution is stable."

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

More Anaconda pros

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

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

"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."

"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."

"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 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."

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

More Dataiku pros

Cons

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

"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."

"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."

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

"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."

"The solution needs more planning tools and capabilities."

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."

"The solution would benefit from offering more automation."

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

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

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

"It also takes up a lot of space."

"Anaconda can't handle heavy workloads."

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

More Anaconda cons

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

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

"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."

"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."

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

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

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

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

More Dataiku cons

Pricing and Cost Advice

"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."

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

"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."

"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."

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

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

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

More IBM SPSS Statistics pricing and cost advice

"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."

"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 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."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

814,649 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Financial Services Firm

17%

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?

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

See all answers

What needs improvement with IBM SPSS Statistics?

In some cases, the product takes time to load a large dataset. They could improve this particular area.

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

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 13% 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

More IBM SPSS Statistics Competitors

Databricks vs Anaconda

Compared 41% of the time

Microsoft Power BI vs Anaconda

Compared 12% of the time

Amazon SageMaker vs Anaconda

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Anaconda

Compared 9% 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 14% 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

October 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

No data available

Dataiku DSS

Learn More

Video not available

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.

DOWNLOAD NOW

814,649 professionals have used our research since 2012.

See our Anaconda vs. Dataiku report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.