Azure OpenAI vs DataRobot comparison

Microsoft and DataRobot are both solutions in the AI Development Platforms category. Microsoft is ranked #1 with an average rating of 7.9, while DataRobot is ranked #12 with an average rating of 8.7. Microsoft holds a 12.9% mindshare in AIDP, compared to DataRobot’s 1.4% mindshare. Additionally, 93% of Microsoft users are willing to recommend the solution, compared to 100% of DataRobot users who would recommend it.

Azure OpenAI

Read 33 Azure OpenAI reviews

8,663 Views
7,905 Comparison Views

93% willing to recommend

DataRobot

Read 5 DataRobot reviews

1,231 Views
560 Comparison Views

100% willing to recommend

Azure OpenAI

DataRobot

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

DataRobot and Azure OpenAI compete in automated machine learning and AI solutions. Azure OpenAI seems superior due to its comprehensive feature offerings, making it a worthwhile investment.

Features: DataRobot focuses on automated machine learning with an emphasis on simplicity and efficiency. It provides a user-friendly interface, comprehensive model building, and deployment tools. Azure OpenAI offers a wide range of AI functionalities with deep integration into the Azure ecosystem, leveraging the strengths of the GPT-3.5 models for natural language processing, document analysis, and scalability, which enhances its capabilities.

Room for Improvement: DataRobot could benefit from expanding its feature set beyond the current offerings and enhancing its integration with other platforms. It may also improve scalability options. Azure OpenAI could improve its deployment complexity by simplifying the setup process. Additionally, addressing its higher cost structure and geographical availability restrictions could attract more users.

Ease of Deployment and Customer Service: DataRobot offers an easy deployment process with dedicated customer support, ideal for businesses looking for quick implementation. Azure OpenAI, backed by the robust Azure infrastructure, provides scalable deployment, although it may involve a steeper learning curve. Its customer service focuses on leveraging Azure's global network to resolve issues effectively.

Pricing and ROI: DataRobot offers competitive pricing with predictable costs, providing a clear ROI through efficient model building and deployment. Azure OpenAI may require a higher initial investment but has potential for significant long-term ROI through advanced features and integration capabilities, promising greater scalability and improved business efficiencies.

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

Buyer's Guide

Azure OpenAI vs. DataRobot

April 2025

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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

Azure OpenAI

Ranking in AI Development Platforms

1st

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

DataRobot

Ranking in AI Development Platforms

12th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

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

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 12.9%, down from 21.1% compared to the previous year. The mindshare of DataRobot is 1.4%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Viswanath Barenkala

Associate Vice President at State Street

Offers tools to moderate generated content and guidance to safely design applications, but it is not consistently accessible

Instead of a feature, the GPT-4 model has been most beneficial for automating tasks. We transitioned from GPT-3.5 to GPT-4 and actively use it. However, we face limitations due to geographic availability, subscription constraints, and rate limiting, which we are currently negotiating and working towards optimizing. While we haven't formally benchmarked Azure OpenAI's language understanding against industry standards, we find it performs well about 70-80% of the time. Occasionally, we need to refine our queries and adapt our systems accordingly to improve accuracy and effectiveness.

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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.

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

"Its versatility makes it incredibly useful for technical problem-solving, content creation, data analytics, and more."

"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."

"I would rate it a nine out of ten."

"Azure OpenAI has significantly reduced costs and increased efficiency in tasks such as aggressive testing of systems to avoid anomalies and trust issues."

"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."

"Two aspects I appreciate are the turnaround time and ease of use. As it's a managed service, the quick turnaround is beneficial, and the simple interface makes it easy to work with. Performance and scalability are also strong points since you can scale as needed."

"Azure OpenAI is easy to use because the endpoints are created, and we just need to pass our parameters and info."

"The most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users."

More Azure OpenAI pros

"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."

"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."

Cons

"Sometimes, it gives answers in English, even when the request is in Polish."

"I noticed there are no instructional videos or guides on the network portal for initial configurations. There is limited information available, and this is a concern for me. I would like to see more resources and guides to address these issues."

"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."

"The UI could be a little easier."

"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."

"The product must improve its dashboards."

"There could be an ability to generate visual data, such as architecture diagrams."

"Maybe with the next release, the response will be more precise and more human-like."

More Azure OpenAI cons

"There are some performance issues."

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

"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."

"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."

Pricing and Cost Advice

"I rate the product pricing six out of ten."

"The cost is quite high and fixed."

"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."

"The licensing is interaction-based, meaning transactional. It's reasonably priced for now."

"The cost structure depends on the volume of data processed and the computational resources required."

"It's a token-based system, so you pay per token used by the model."

"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."

"The solution's pricing depends on the services you will deploy."

More Azure OpenAI 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."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

11%

Educational Organization

19%

Financial Services Firm

13%

Manufacturing Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Azure OpenAI?

The product is easy to integrate with our IT workflow.

See all answers

What is your experience regarding pricing and costs for Azure OpenAI?

In the past, the primary expense involved token limitations which constrained scaling. Recent iterations have increased token allowances, mitigating some challenges associated with concurrent user ...

See all answers

What needs improvement with Azure OpenAI?

Azure ( /products/microsoft-azure-reviews ) could significantly benefit from including more LLM models apart from OpenAI, as I often need to switch clouds when a model doesn't meet my requirements....

See all answers

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.

See all answers

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...

See all answers

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...

See all answers

Comparisons

Google Vertex AI vs Azure OpenAI

Compared 42% of the time

Hugging Face vs Azure OpenAI

Compared 13% of the time

Amazon SageMaker vs Azure OpenAI

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Azure OpenAI

Compared 8% of the time

Google Cloud AI Platform vs Azure OpenAI

Compared 8% of the time

More Azure OpenAI Competitors

Amazon SageMaker vs DataRobot

Compared 36% of the time

Datadog vs DataRobot

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs DataRobot

Compared 11% of the time

Altair RapidMiner vs DataRobot

Compared 10% of the time

Alteryx vs DataRobot

Compared 8% of the time

More DataRobot Competitors

Product Reports

Buyer's Guide

Azure OpenAI

April 2025

Download Azure OpenAI product report

Buyer's Guide

Predictive Analytics

March 2025

Download DataRobot product report

Overview

Azure OpenAI integrates advanced language models with robust security for precise information extraction and task automation. Its seamless Azure integration and drag-and-drop interface simplify implementation and enhance accessibility.

Azure OpenAI offers a comprehensive suite of features designed for efficient data processing and task automation. It provides high precision in extracting information and strong conversational capabilities, crucial for developing chatbots and customer support systems. Its integration with Azure ensures seamless data handling and security, addressing key enterprise requirements. Users can employ its versatile GPT models for diverse applications such as predictive analytics, summarizing large documents, and competitive benchmarking. Despite its strengths, it faces challenges like latency, inadequate regional support, and limited integration of new technologies. Improvements in model fine-tuning and more flexible configuration are desired by users.

What features make Azure OpenAI a reliable choice?

High Precision: Ensures accurate data extraction suitable for critical applications.
Conversational Capabilities: Facilitates the creation of sophisticated chatbots.
Azure Integration: Seamlessly connects with Azure services for enhanced functionality.
Automation Support: Automates repetitive tasks, improving efficiency.
Security Features: Offers robust protection for sensitive data.
Drag-and-Drop Environment: Simplifies user interaction and deployment.

What benefits and ROI should users consider?

Natural Language Processing: Provides superior language model performance.
Quick Implementation: Reduces time to deploy applications.
Scalability: Supports growing business needs with ease.
Versatile GPT Models: Applicable across different industry workflows.

Azure OpenAI is implemented across industries like healthcare, finance, and education for tasks like invoice processing, digitalizing records, and language translation. It enhances policy management, document assimilation, and customer support with predictive analytics and keyword extraction. Organizations in such sectors benefit from streamlined workflows and task automation.

Microsoft

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

Sample Customers

Information Not Available

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

Buyer's Guide

Azure OpenAI vs. DataRobot

April 2025

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