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DataRobot vs Hugging Face 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
13th
Average Rating
8.6
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
Predictive Analytics (5th), AIOps (14th)
Hugging Face
Ranking in AI Development Platforms
5th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2025, in the AI Development Platforms category, the mindshare of DataRobot is 1.3%, up from 1.0% compared to the previous year. The mindshare of Hugging Face is 13.2%, up from 6.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Raviteja Guna - PeerSpot reviewer
Highly automated solution allowing data scientists to build models easily
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Even the documentation is well-maintained in terms of its capabilities. It's easy to navigate. The support documents are good. Even someone with basic IT knowledge can easily navigate. If you're an IT engineer, you can efficiently perform operations using it. We have deployed eight to nine use cases on DataRobot and have seen a tremendous response in accuracy and performance. We are pleased because we conducted a comparison. We took a model we built using a sample Python on a local machine and applied the same data and process using DataRobot Autopilot. The results were pretty amazing, with promising accuracy and recall. The accessibility is so easy. Even a college graduate with essential experience can use it. Suppose I do the same model in Databricks and want to monitor my MLOps pipeline. So, I need to use a third-party framework again, like MLflow, Kubeflow, Airflow, or whatever. I need to build my dashboards and everything, customization dashboards. However, everything is available in DataRobot. I can use it directly. They have a new option called DataRobot apps. So, on the predictions, we can even create customized apps. I can build my dashboard, and I can develop my applications. Overall, I rate the solution an eight out of ten.
SwaminathanSubramanian - PeerSpot reviewer
Versatility empowers AI concept development despite the multi-GPU challenge
Regarding scalability, I'm finding the multi-GPU aspect of it challenging. Training the model is another hurdle, although I'm only getting into that aspect currently. Organizations are apprehensive about investing in multi-GPU setups. Additionally, data cleanup is a challenge that needs to be resolved, as data must be mature and pristine.

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."
"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."
"DataRobot is highly automated, allowing data scientists to build models easily."
"DataRobot can be easy to use."
"The tool's most valuable feature is that it shows trending models. All the new models, even Google's demo models, appear at the top. You can find all the open-source models in one place. You can use them directly and easily find their documentation. It's very simple to find documentation and write code. If you want to work with AI and machine learning, Hugging Face is a perfect place to start."
"I like that Hugging Face is versatile in the way it has been developed."
"What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."
"Hugging Face provides open-source models, making it the best open-source and reliable solution."
"My preferred aspects are natural language processing and question-answering."
"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."
"I would rate this product nine out of ten."
"The product is reliable."
 

Cons

"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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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."
"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."
"There are some performance issues."
"I believe Hugging Face has some room for improvement. There are some security issues. They provide code, but API tokens aren't indicated. Also, the documentation for particular models could use more explanation. But I think these things are improving daily. The main change I'd like to see is making the deployment of inference endpoints more customizable for users."
"Implementing a cloud system to showcase historical data would be beneficial."
"It can incorporate AI into its services."
"The solution must provide an efficient LLM."
"Access to the models and datasets could be improved. Many interesting ones are restricted."
"Most people upload their pre-trained models on Hugging Face, but more details should be added about the models."
"Initially, I faced issues with the solution's configuration."
"Access to the models and datasets could be improved."
 

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."
"So, it's requires expensive machines to open services or open LLM models."
"The tool is open-source. The cost depends on what task you're doing. If you're using a large language model with around 12 million parameters, it will cost more. On average, Hugging Face is open source so you can download models to your local machine for free. For deployment, you can use any cloud service."
"Hugging Face is an open-source solution."
"We do not have to pay for the product."
"The solution is open source."
"I recall seeing a fee of nine dollars, and there's also an enterprise option priced at twenty dollars per month."
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Top Industries

By visitors reading reviews
Educational Organization
24%
Financial Services Firm
13%
Computer Software Company
8%
Manufacturing Company
8%
Computer Software Company
10%
Manufacturing Company
10%
Financial Services Firm
10%
University
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What needs improvement with DataRobot?
There are some performance issues when it comes to improvements. They also offer storage-related services compared to other tools like Admin, Azure, or AWS. It is easy to plug and play. Third-party...
What is your primary use case for DataRobot?
We work on AI and ML use cases related to technology and IT.
What advice do you have for others considering DataRobot?
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Eve...
What do you like most about Hugging Face?
My preferred aspects are natural language processing and question-answering.
What needs improvement with Hugging Face?
Access to the models and datasets could be improved. Many interesting ones are restricted. It would be great if they provided access for students or non-professionals who just want to test things.
What is your primary use case for Hugging Face?
This is a simple personal project, non-commercial. As a student, that's all I do.
 

Comparisons

 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Information Not Available
Find out what your peers are saying about DataRobot vs. Hugging Face and other solutions. Updated: January 2025.
838,533 professionals have used our research since 2012.