DataRobot vs TensorFlow comparison

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DataRobot

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Executive SummaryUpdated on Dec 4, 2024

DataRobot and TensorFlow are competing in the AI and machine learning space, each targeting different needs. DataRobot offers an edge in ease of use and rapid deployment, while TensorFlow provides robust features and scalability for technical experts seeking advanced customization.

Features:DataRobot features automated model building, user-friendly operation without requiring extensive programming skills, and strong predictive analytics. TensorFlow provides a flexible framework, broad applicability for deep learning tasks, and scalability for handling large datasets and complex models.

Room for Improvement:DataRobot could enhance its features for comprehensive data processing, expand its customization options, and improve open-source integration. TensorFlow might focus on simplifying its deployment process for non-technical users, enhancing its user interface, and improving efficiency in training on smaller datasets.

Ease of Deployment and Customer Service:DataRobot facilitates a quick deployment process with extensive support appealing to non-technical users. TensorFlow requires more technical expertise for deployment but offers abundant community resources and detailed documentation.

Pricing and ROI:DataRobot generally has higher initial setup costs but offers rapid ROI through its automated features and predictive tools. TensorFlow, being open-source, has low initial costs, shifting ROI focus to the development expertise required. It remains cost-effective for those investing in technical resources for custom model development.

To learn more, read our detailed DataRobot vs. TensorFlow Report (Updated: April 2025).

DataRobot vs. TensorFlow

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Review summaries and opinions

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

Categories and Ranking

DataRobot

Ranking in AI Development Platforms

13th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Predictive Analytics (5th), AIOps (16th)

TensorFlow

Ranking in AI Development Platforms

6th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the AI Development Platforms category, the mindshare of DataRobot is 1.4%, up from 1.1% compared to the previous year. The mindshare of TensorFlow is 3.8%, down from 6.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

SagarYadav

Staff Specialist Data Scientist at BMC Software, Inc.

Automating model comparison speeds up development and reduces timelines

DataRobot is equipped with a GUI-based approach that simplifies the process of feature engineering and model training. It provides AutoML capabilities, which allow for comparing thousands of models and selecting the best-suited one based on business requirements. By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.

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Ashish Upadhyay

Founder at BlockMosiac

A robust tools for model visualization and debugging with superior scalability and stability, and an intuitive user-friendly interface

The one feature we find most valuable at our company is its robust and flexible machine-learning capabilities. It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions. The ability to develop and fine-tune models, such as risk assessment for detection and market protection, as well as the creation of recommendation systems, is paramount. This versatility extends to providing personalized identity-relevant applications for our enterprise clients, delivering valuable insights to the market. Its exceptional support for deep learning and its efficient resource utilization enable us to undertake complex financial and data analyses. The flexibility it provides is crucial for meeting industrial requirements and crafting solutions tailored to our client's specific needs.

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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

"DataRobot is highly automated, allowing data scientists to build models easily."

"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."

"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."

"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."

"DataRobot can be easy to use."

"It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions."

"TensorFlow provides Insights into both data and machine learning strategies."

"Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment."

"TensorFlow is a framework that makes it really easy to use for deep learning."

"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."

"It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models."

"TensorFlow is easy to implement and offers inbuilt functions for various tasks."

"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."

More TensorFlow pros

Cons

"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."

"DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality."

"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."

"There are some performance issues."

"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."

"The solution is hard to integrate with the GPUs."

"For newcomers to the field, the learning curve can be steep, often requiring about a year of dedicated effort."

"JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow."

"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."

"The process of creating models could be more user-friendly."

"It currently offers inbuilt functions, however, having the ability to implement custom libraries would enhance its usefulness for enterprise-level applications."

"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications."

"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."

More TensorFlow cons

Pricing and Cost Advice

"The price of DataRobot is good because if you take the price of the solution which is approximately $65,000, it is less than a data scientist. There are very few data scientists available."

"We dropped the plan to use DataRobot, because we found the pricing to be on the higher sise. We liked DataRobot a lot, but due to the pricing, we dropped that idea."

"TensorFlow is free."

"We are using the free version."

"I did not require a license for this solution. It a free open-source solution."

"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."

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

"The solution is free."

"I am using the open-source version of TensorFlow and it is free."

"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."

More TensorFlow pricing and cost advice

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Top Industries

By visitors reading reviews

Educational Organization

18%

Financial Services Firm

13%

Manufacturing Company

Computer Software Company

Manufacturing Company

14%

Computer Software Company

13%

University

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What needs improvement with DataRobot?

DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality.

What is your primary use case for DataRobot?

In our day-to-day use, I utilize DataRobot to speed up our development process through its GUI capability. Once I set up our connection with a back-end data set, whatever the project I work on next...

What advice do you have for others considering DataRobot?

I would recommend DataRobot because if there is something not included in the UI, I have the freedom to use its Python API, which extends the capability for different use cases. Additionally, I wou...

What do you like most about TensorFlow?

It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions.

What is your experience regarding pricing and costs for TensorFlow?

I am not familiar with the pricing setup cost and licensing.

What needs improvement with TensorFlow?

Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currently offers inbuilt functions, however, having the ability to implement custom libr...

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Product Reports

Predictive Analytics

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Overview

DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.

DataRobot

TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant

Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm

DataRobot vs. TensorFlow