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 11.8% 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 SummaryUpdated on Dec 5, 2024

Anaconda and Dataiku are competing products in the data science and analytics market. Anaconda often holds the advantage in flexibility and package availability, while Dataiku is preferred for automation and collaboration.

Features: Anaconda provides a comprehensive range of data science packages, flexibility for custom development, and a robust community for tech-savvy users. It supports multiple programming languages and integrates tools like Jupyter and Spider. Dataiku offers a user-friendly environment for automating workflows, providing seamless integration and easy collaboration among team members. Its platform suits both coders and non-coders with click or code flexibility, making it ideal for collaborative environment settings.

Room for Improvement: Anaconda could enhance pre-built model repositories to aid developers in trying specific models. The learning curve for beginners could be reduced with more intuitive onboarding and tutorials. It may also benefit from improved integration with non-Python environments. Dataiku can expand its customization options for technical users looking for deeper control. Integration with a wider range of third-party applications would benefit its platform. The visual interface could offer more advanced features for experienced data scientists.

Ease of Deployment and Customer Service: Anaconda features a straightforward deployment model, supported by its active community, making it ideal for customizable environments. Dataiku provides a more guided deployment process with comprehensive support services, prioritizing ease of integration and deployment efficiency. Its approach ensures a smoother implementation process with support readily available for users.

Pricing and ROI: Anaconda offers a cost-effective setup with numerous open-source tools, leading to lower initial investment but possibly requiring more resources for maintenance. Dataiku involves higher upfront costs yet provides faster ROI due to its ease of use, automation capabilities, and streamlined processes. Its pricing model reflects the value added through quicker deployment and reduced operational complexity.

To learn more, read our detailed Anaconda vs. Dataiku Report (Updated: December 2024).

Buyer's Guide

Anaconda vs. Dataiku

December 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of December 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.7%, up from 2.7% 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 11.8%, up from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts

I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.

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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

"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."

"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."

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

"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."

"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."

"The most valuable feature is its robust statistical analysis capabilities."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

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

More IBM SPSS Statistics pros

"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."

"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."

"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."

"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 most advantageous feature is the logic building."

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

"The virtual environment is very good."

More Anaconda pros

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

"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."

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

"The solution is quite stable."

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

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

"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."

More Dataiku pros

Cons

"The reports could be better."

"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."

"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."

"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."

"Better documentation on how to use macros."

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

"The design of the experience can be improved."

More IBM SPSS Statistics cons

"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."

"Having a small guide or video on the tool would help learn how to use it and what the features are."

"It also takes up a lot of space."

"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."

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

"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."

"Anaconda should be optimized for RAM consumption."

More Anaconda cons

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

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

"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."

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

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

"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."

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

More Dataiku cons

Pricing and Cost Advice

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

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

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

"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."

"The price of IBM SPSS Statistics could improve."

"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

"The tool is open-source."

"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."

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

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

19%

Computer Software Company

10%

University

Manufacturing Company

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.

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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...

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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...

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What needs improvement with Anaconda?

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

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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 16% of the time

Alteryx 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 11% 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 12% of the time

Microsoft Azure Machine Learning Studio vs Anaconda

Compared 9% of the time

More Anaconda Competitors

Databricks vs Dataiku

Compared 37% 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

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Anaconda

December 2024

Download Anaconda product report

Buyer's Guide

Dataiku

December 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

December 2024

Free Report: Anaconda vs. Dataiku

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

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