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DataRobot vs TensorFlow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

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
15th
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
7
Ranking in other categories
Predictive Analytics (5th), AIOps (15th), AI Observability (72nd), AI Finance & Accounting (7th)
TensorFlow
Ranking in AI Development Platforms
8th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
19
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the AI Development Platforms category, the mindshare of DataRobot is 2.0%, up from 1.3% compared to the previous year. The mindshare of TensorFlow is 5.3%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
TensorFlow5.3%
DataRobot2.0%
Other92.7%
AI Development Platforms
 

Featured Reviews

Naqash Ahmed - PeerSpot reviewer
Senior Data Reporting Analyst at University of Bradford
Automation has improved efficiency and decision-making while big data handling and transparency still need work
Aside from the many advantages of DataRobot, I believe there are areas that could be improved based on my experience. There is a lack of transparency in the models; sometimes it feels like a black box. For example, when I uploaded a large data set of about two gigabytes for processing, the time taken was slower than expected. Additionally, the handling of bigger data sets could be better, as it performs extremely well with smaller datasets but can lag with larger ones. The integration with some other tools used in our organization can also be challenging, and more flexibility for custom pre-processing and advanced model tuning would be beneficial. In terms of support and documentation, I believe improvements are needed. For instance, the response time from DataRobot could be quicker, which would be appreciated when we need assistance. The documentation is generally sufficient, but it can be lengthy and could use more real-world examples and step-by-step tutorials for better clarity. Lastly, creating a client community where users can share experiences and solutions might enhance the overall value and learning curve.
TJ
Owner at Go knowledge
Has good stability, but the process of creating models could be more user-friendly
The platform integrates well with other tools, especially Python, which we use to create models. These models can be deployed on mobile devices, which perfectly suits our requirements. It supports our AI-driven initiatives very well by producing AI models, which is its primary function. I recommend it for those seeking specialized scripting. However, it's important to consider other options as well. It is better suited for specialists in the field and is less user-friendly than general tools like Excel. I rate it overall at six out of ten. While it is a powerful tool, other software options are slightly simpler for training models.

Quotes from Members

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

Pros

"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 has positively impacted my organization, and since we started using this tool, we have automated several legacy models with far better performance."
"DataRobot can be easy to use."
"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."
"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."
"DataRobot is highly automated, allowing data scientists to build models easily."
"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."
"Tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"TensorFlow has benefitted us by enabling faster training and deployment."
"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."
"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."
"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."
"I would rate the solution an eight out of ten. I am not a developer but more of an account manager. I can find what I want with TensorFlow. I haven’t contacted technical support for any issues. Since TensorFlow is vastly documented on the internet, I usually find some good websites where people exchange their views about the solution and apply that."
"The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing."
"We haven't had any issues stability-wise or scalability-wise."
 

Cons

"There is a lack of transparency in the models; sometimes it feels like a black box."
"The price points can also be improved."
"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."
"All the others can use it, but not to the maximum."
"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."
"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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"We dropped the plan to use DataRobot because we found the pricing to be on the higher side."
"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."
"The process of creating models could be more user-friendly."
"I utilize a Mac, and I am unable to utilize AMD GPUs."
"I know this is out of the scope of TensorFlow, however, every time I've sent a request, I had to renew the model into RAM and they didn't make that prediction or inference. This makes the point for the request that much longer. If they could provide anything to help in this part, it will be very great."
"TensorFlow deep learning takes a lot of computation power."
"There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"Providing more control by allowing users to build custom functions would make TensorFlow a better option."
 

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."
"I rate TensorFlow's pricing a five out of ten."
"We are using the free version."
"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."
"I am using the open-source version of TensorFlow and it is free."
"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
"I did not require a license for this solution. It a free open-source solution."
"TensorFlow is free."
"The solution is free."
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Top Industries

By visitors reading reviews
Manufacturing Company
13%
Financial Services Firm
13%
Educational Organization
9%
Computer Software Company
8%
Manufacturing Company
15%
Comms Service Provider
9%
University
9%
Financial Services Firm
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise5
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise3
 

Questions from the Community

What is your experience regarding pricing and costs for DataRobot?
My experience with pricing, setup cost, and licensing reveals that the price points can be improved and DataRobot is not so cost-effective, especially for smaller organizations.
What needs improvement with DataRobot?
To improve DataRobot, I suggest enhancing model accuracy metrics and improving automation. The price points can also be improved. Another improvement that DataRobot needs is integrating the capabil...
What is your primary use case for DataRobot?
DataRobot serves as our data science platform for building machine learning models and the development environment for running models. We also use the best practice processes and governance that Da...
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...
What is your primary use case for TensorFlow?
I've used TensorFlow for image classification tasks, object detection tasks, and OCR.
 

Comparisons

 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
Find out what your peers are saying about DataRobot vs. TensorFlow and other solutions. Updated: March 2026.
885,286 professionals have used our research since 2012.