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 9.0. Microsoft holds a 22.2% mindshare in AIDP, compared to DataRobot’s 1.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of DataRobot users who would recommend it.

Azure OpenAI

Read 30 Azure OpenAI reviews

8,392 Views
7,803 Comparison Views

92% willing to recommend

DataRobot

Read 4 DataRobot reviews

1,090 Views
498 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: December 2024).

Buyer's Guide

Azure OpenAI vs. DataRobot

December 2024

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Categories and Ranking

Azure OpenAI

Ranking in AI Development Platforms

1st

Average Rating

8.0

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

7.1

Number of Reviews

Ranking in other categories

Predictive Analytics (5th), AIOps (17th)

Mindshare comparison

As of December 2024, in the AI Development Platforms category, the mindshare of Azure OpenAI is 22.2%, up from 18.4% compared to the previous year. The mindshare of DataRobot is 1.7%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Anup Karade

Associate Vice President at LTIMindtree

Created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions

We have created our own platform called CanvasAI. It provides machine-learning plumbing and integration with your services. So, we've integrated Azure OpenAI through Canvas. We're also looking at some hard interface modeling from AWS as well. We access Azure OpenAI solutions for our business workflow via the platform, not directly from the service provider. There are security considerations we're working through with the security team, etc. Canvas provides the control plane, which handles RBAC for user registration and model management. For internal processes, we're using OpenAI to create partner call reports, like summarizing quarterly zip code data and other financial models. We also use it for legal and contract stuff, like comparing SOWs and contracts. For user experience, we've created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions.

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Raviteja Guna

Data Scientist at a tech services company with 10,001+ employees

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.

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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

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

"The product saves a lot of time."

"OpenAI's models are more mature than Watson's. They offer a wider range of features and provide richer outputs."

"The product's initial setup phase was pretty easy."

"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."

"Azure OpenAI is very easy to use instead of AWS services."

"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."

"The high precision of information extraction is the most valuable feature."

More Azure OpenAI pros

"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."

"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."

Cons

"The fine-tuning of models with the use of Azure OpenAI is an area with certain shortcomings currently, and it can be considered for improvement in the future."

"The solution's response is a bit slow sometimes."

"One major drawback of Azure OpenAI is its availability, as it's not consistently accessible for effective use."

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

"I faced one issue with Azure OpenAI: My customer wanted more clarity on the pricing. They were not able to get proper answers from the documentation or the pricing calculator. I suggest that Microsoft maintain standardization in the pricing details published in the documentation and the pricing calculator."

"Sometimes, the responses are repetitive."

"Deployment was slightly complex for me to understand."

"In the next release, they could enhance the product's features for even greater usability and efficiency."

More Azure OpenAI cons

"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."

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

"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."

Pricing and Cost Advice

"Regarding pricing and licensing, it's a bit complex due to the minimum purchase requirement for PTO units. We're evaluating the best approach between PTE and pay-as-you-go models. Our organization is cautious about committing to PTE due to the fixed bandwidth reservation, while pay-as-you-go doesn't offer enough flexibility. We're discussing these matters with legal teams to ensure compliance and data security."

"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."

"Cost-wise, the product's price is a bit on the higher side."

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

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

"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."

"Azure OpenAI is a bit more expensive than other services."

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

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

25%

Financial Services Firm

12%

Computer Software Company

Manufacturing 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?

The pricing really depends on the specific requirements and underlying needs. For example, if the goal is to implement innovative solutions for the future or to improve productivity in decision-mak...

See all answers

What needs improvement with Azure OpenAI?

For my needs, when working with interactive dashboards, it's expensive. I would prefer a system that provides alternative dashboard options or allows me to go directly into the program and pinpoint...

See all answers

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...

See all answers

What is your primary use case for DataRobot?

We work on AI and ML use cases related to technology and IT.

See all answers

What advice do you have for others considering DataRobot?

See all answers

Comparisons

Google Vertex AI vs Azure OpenAI

Compared 47% of the time

Amazon SageMaker vs Azure OpenAI

Compared 11% of the time

Hugging Face vs Azure OpenAI

Compared 11% of the time

Microsoft Azure Machine Learning Studio vs Azure OpenAI

Compared 9% of the time

AI21 Studio vs Azure OpenAI

Compared 0% of the time

More Azure OpenAI Competitors

Amazon SageMaker vs DataRobot

Compared 32% of the time

Datadog vs DataRobot

Compared 14% of the time

Microsoft Azure Machine Learning Studio vs DataRobot

Compared 13% of the time

RapidMiner vs DataRobot

Compared 12% of the time

SAS Predictive Analytics vs DataRobot

Compared 4% of the time

More DataRobot Competitors

Product Reports

Buyer's Guide

Azure OpenAI

December 2024

Download Azure OpenAI product report

Buyer's Guide

Predictive Analytics

December 2024

Download DataRobot product report

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Microsoft

DataRobot

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.

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.

Sample Customers

Information Not Available

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

Buyer's Guide

Azure OpenAI vs. DataRobot

December 2024

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