# Top 10 Azure Machine Learning Alternatives & Competitors
**Average Rating:** 4.3/5
**Total Number of Reviews:** 90
If you are considering Azure Machine Learning, you may also want to investigate similar alternatives or competitors to find the best solution. Data Science and Machine Learning Platforms is a widely used technology, and many people are seeking innovative, easy to use software solutions with drag and drop, pre-built algorithms, and model training. Other important factors to consider when researching alternatives to Azure Machine Learning include user interface and features. The best overall Azure Machine Learning alternative is Gemini Enterprise Agent Platform. Other similar apps like Azure Machine Learning are Dataiku, Amazon SageMaker, Altair AI Studio, and Alteryx. Azure Machine Learning alternatives can be found in [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) but may also be in [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) or [Analytics Platforms](https://www.g2.com/categories/analytics-platforms).


## Best Paid & Free Alternatives to Azure Machine Learning
  - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)
  - [Dataiku](https://www.g2.com/products/dataiku/reviews)
  - [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews)
  - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews)
  - [Alteryx](https://www.g2.com/products/alteryx/reviews)
  - [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews)
  - [MATLAB](https://www.g2.com/products/matlab/reviews)
  - [DataRobot](https://www.g2.com/products/datarobot/reviews)
  - [Google Cloud AutoML](https://www.g2.com/products/google-cloud-automl/reviews)
  - [Databricks](https://www.g2.com/products/databricks/reviews)

## Top 10 Alternatives to Azure Machine Learning Recently Reviewed By G2 Community
Browse options below. Based on reviewer data, you can see how Azure Machine Learning stacks up to the competition, check reviews from current & previous users in industries like Information Technology and Services, Education Management, and Hospital & Health Care, and find the best product for your business.


  ### 1. [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)
By Google
**Average Rating:** 4.3/5
**Total Reviews:** 659
Gemini Enterprise Agent Platform is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Gemini Enterprise Agent Platform Workbench is a cloud-based IDE that is included with Gemini Enterprise Agent Platform. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Gemini Enterprise Agent Platform and Gemini Enterprise Agent Platform Workbench are a powerful combination that can help you accelerate your ML development. With Gemini Enterprise Agent Platform, you can focus on building and training your models, while Gemini Enterprise Agent Platform Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Gemini Enterprise Agent Platform is a great option. With Gemini Enterprise Agent Platform, you can build, train, and deploy ML models faster and easier than ever before.


Reviewers say compared to Azure Machine Learning, Gemini Enterprise Agent Platform is:
- More expensive
- Better at meeting requirements
Categories in common with Azure Machine Learning: [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Large Language Model Operationalization (LLMOps)](https://www.g2.com/categories/large-language-model-operationalization-llmops), [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Generative AI Infrastructure](https://www.g2.com/categories/generative-ai-infrastructure), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-gemini-enterprise-agent-platform)
**Compare Gemini Enterprise Agent Platform with other alternatives:**
- [Gemini Enterprise Agent Platform vs Dataiku](https://www.g2.com/compare/dataiku-vs-gemini-enterprise-agent-platform)
- [Gemini Enterprise Agent Platform vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-gemini-enterprise-agent-platform)
- [Gemini Enterprise Agent Platform vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-gemini-enterprise-agent-platform)
- [Gemini Enterprise Agent Platform vs Alteryx](https://www.g2.com/compare/alteryx-vs-gemini-enterprise-agent-platform)
- [Gemini Enterprise Agent Platform vs IBM Watson Studio](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-ibm-watson-studio)
- [Gemini Enterprise Agent Platform vs MATLAB](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-matlab)
- [Gemini Enterprise Agent Platform vs DataRobot](https://www.g2.com/compare/datarobot-vs-gemini-enterprise-agent-platform)
- [Gemini Enterprise Agent Platform vs Google Cloud AutoML](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-google-cloud-automl)
- [Gemini Enterprise Agent Platform vs Databricks](https://www.g2.com/compare/databricks-vs-gemini-enterprise-agent-platform)

  ### 2. [Dataiku](https://www.g2.com/products/dataiku/reviews)
By Dataiku
**Average Rating:** 4.4/5
**Total Reviews:** 221
Dataiku is the Universal AI Platform, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents.


Reviewers say compared to Azure Machine Learning, Dataiku is:
- Slower to reach roi
- More expensive
- More usable
Categories in common with Azure Machine Learning: [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Large Language Model Operationalization (LLMOps)](https://www.g2.com/categories/large-language-model-operationalization-llmops), [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Generative AI Infrastructure](https://www.g2.com/categories/generative-ai-infrastructure), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Dataiku](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-dataiku)
**Compare Dataiku with other alternatives:**
- [Dataiku vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/dataiku-vs-gemini-enterprise-agent-platform)
- [Dataiku vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-dataiku)
- [Dataiku vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-dataiku)
- [Dataiku vs Alteryx](https://www.g2.com/compare/alteryx-vs-dataiku)
- [Dataiku vs IBM Watson Studio](https://www.g2.com/compare/dataiku-vs-ibm-watson-studio)
- [Dataiku vs MATLAB](https://www.g2.com/compare/dataiku-vs-matlab)
- [Dataiku vs DataRobot](https://www.g2.com/compare/datarobot-vs-dataiku)
- [Dataiku vs Google Cloud AutoML](https://www.g2.com/compare/dataiku-vs-google-cloud-automl)
- [Dataiku vs Databricks](https://www.g2.com/compare/databricks-vs-dataiku)

  ### 3. [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews)
By Amazon Web Services (AWS)
**Average Rating:** 4.3/5
**Total Reviews:** 56
Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.


Reviewers say compared to Azure Machine Learning, Amazon SageMaker is:
- Slower to reach roi
- More expensive
- Easier to do business with
Categories in common with Azure Machine Learning: [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Generative AI Infrastructure](https://www.g2.com/categories/generative-ai-infrastructure), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-microsoft-azure-machine-learning)
**Compare Amazon SageMaker with other alternatives:**
- [Amazon SageMaker vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/amazon-sagemaker-vs-gemini-enterprise-agent-platform)
- [Amazon SageMaker vs Dataiku](https://www.g2.com/compare/amazon-sagemaker-vs-dataiku)
- [Amazon SageMaker vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-amazon-sagemaker)
- [Amazon SageMaker vs Alteryx](https://www.g2.com/compare/alteryx-vs-amazon-sagemaker)
- [Amazon SageMaker vs IBM Watson Studio](https://www.g2.com/compare/amazon-sagemaker-vs-ibm-watson-studio)
- [Amazon SageMaker vs MATLAB](https://www.g2.com/compare/amazon-sagemaker-vs-matlab)
- [Amazon SageMaker vs DataRobot](https://www.g2.com/compare/amazon-sagemaker-vs-datarobot)
- [Amazon SageMaker vs Google Cloud AutoML](https://www.g2.com/compare/amazon-sagemaker-vs-google-cloud-automl)
- [Amazon SageMaker vs Databricks](https://www.g2.com/compare/amazon-sagemaker-vs-databricks)

  ### 4. [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews)
By Altair
**Average Rating:** 4.6/5
**Total Reviews:** 520
RapidMiner is a powerful, easy to use and intuitive graphical user interface for the design of analytic processes. Let the Wisdom of Crowds and recommendations from the RapidMiner community guide your way. And you can easily reuse your R and Python code.


Reviewers say compared to Azure Machine Learning, Altair AI Studio is:
- Easier to set up
- More usable
- Easier to do business with
Categories in common with Azure Machine Learning: [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Generative AI Infrastructure](https://www.g2.com/categories/generative-ai-infrastructure), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-microsoft-azure-machine-learning)
**Compare Altair AI Studio with other alternatives:**
- [Altair AI Studio vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/rapidminer-studio-vs-gemini-enterprise-agent-platform)
- [Altair AI Studio vs Dataiku](https://www.g2.com/compare/rapidminer-studio-vs-dataiku)
- [Altair AI Studio vs Amazon SageMaker](https://www.g2.com/compare/rapidminer-studio-vs-amazon-sagemaker)
- [Altair AI Studio vs Alteryx](https://www.g2.com/compare/rapidminer-studio-vs-alteryx)
- [Altair AI Studio vs IBM Watson Studio](https://www.g2.com/compare/rapidminer-studio-vs-ibm-watson-studio)
- [Altair AI Studio vs MATLAB](https://www.g2.com/compare/rapidminer-studio-vs-matlab)
- [Altair AI Studio vs DataRobot](https://www.g2.com/compare/rapidminer-studio-vs-datarobot)
- [Altair AI Studio vs Google Cloud AutoML](https://www.g2.com/compare/rapidminer-studio-vs-google-cloud-automl)
- [Altair AI Studio vs Databricks](https://www.g2.com/compare/rapidminer-studio-vs-databricks)

  ### 5. [Alteryx](https://www.g2.com/products/alteryx/reviews)
By Alteryx
**Average Rating:** 4.6/5
**Total Reviews:** 877
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.


Reviewers say compared to Azure Machine Learning, Alteryx is:
- More expensive
- Easier to do business with
- Better at meeting requirements
Categories in common with Azure Machine Learning: [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Alteryx](https://www.g2.com/compare/alteryx-vs-microsoft-azure-machine-learning)
**Compare Alteryx with other alternatives:**
- [Alteryx vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/alteryx-vs-gemini-enterprise-agent-platform)
- [Alteryx vs Dataiku](https://www.g2.com/compare/alteryx-vs-dataiku)
- [Alteryx vs Amazon SageMaker](https://www.g2.com/compare/alteryx-vs-amazon-sagemaker)
- [Alteryx vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-alteryx)
- [Alteryx vs IBM Watson Studio](https://www.g2.com/compare/alteryx-vs-ibm-watson-studio)
- [Alteryx vs MATLAB](https://www.g2.com/compare/alteryx-vs-matlab)
- [Alteryx vs DataRobot](https://www.g2.com/compare/alteryx-vs-datarobot)
- [Alteryx vs Google Cloud AutoML](https://www.g2.com/compare/alteryx-vs-google-cloud-automl)
- [Alteryx vs Databricks](https://www.g2.com/compare/alteryx-vs-databricks)

  ### 6. [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews)
By IBM
**Average Rating:** 4.2/5
**Total Reviews:** 168
IBM Watson Studio accelerates the machine and deep learning workflows required to infuse AI into your business to drive innovation. It provides a suite of tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy models at scale.


Reviewers say compared to Azure Machine Learning, IBM Watson Studio is:
- Slower to reach roi
- More expensive
Categories in common with Azure Machine Learning: [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs IBM Watson Studio](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-ibm-watson-studio)
**Compare IBM Watson Studio with other alternatives:**
- [IBM Watson Studio vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-ibm-watson-studio)
- [IBM Watson Studio vs Dataiku](https://www.g2.com/compare/dataiku-vs-ibm-watson-studio)
- [IBM Watson Studio vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-ibm-watson-studio)
- [IBM Watson Studio vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-ibm-watson-studio)
- [IBM Watson Studio vs Alteryx](https://www.g2.com/compare/alteryx-vs-ibm-watson-studio)
- [IBM Watson Studio vs MATLAB](https://www.g2.com/compare/ibm-watson-studio-vs-matlab)
- [IBM Watson Studio vs DataRobot](https://www.g2.com/compare/datarobot-vs-ibm-watson-studio)
- [IBM Watson Studio vs Google Cloud AutoML](https://www.g2.com/compare/google-cloud-automl-vs-ibm-watson-studio)
- [IBM Watson Studio vs Databricks](https://www.g2.com/compare/databricks-vs-ibm-watson-studio)

  ### 7. [MATLAB](https://www.g2.com/products/matlab/reviews)
By MathWorks
**Average Rating:** 4.5/5
**Total Reviews:** 770
MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.


Reviewers say compared to Azure Machine Learning, MATLAB is:
- Slower to reach roi
- More expensive
- Better at meeting requirements
Categories in common with Azure Machine Learning: [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs MATLAB](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-matlab)
**Compare MATLAB with other alternatives:**
- [MATLAB vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-matlab)
- [MATLAB vs Dataiku](https://www.g2.com/compare/dataiku-vs-matlab)
- [MATLAB vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-matlab)
- [MATLAB vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-matlab)
- [MATLAB vs Alteryx](https://www.g2.com/compare/alteryx-vs-matlab)
- [MATLAB vs IBM Watson Studio](https://www.g2.com/compare/ibm-watson-studio-vs-matlab)
- [MATLAB vs DataRobot](https://www.g2.com/compare/datarobot-vs-matlab)
- [MATLAB vs Google Cloud AutoML](https://www.g2.com/compare/google-cloud-automl-vs-matlab)
- [MATLAB vs Databricks](https://www.g2.com/compare/databricks-vs-matlab)

  ### 8. [DataRobot](https://www.g2.com/products/datarobot/reviews)
By DataRobot
**Average Rating:** 4.4/5
**Total Reviews:** 28
DataRobot offers a machine learning platform for data scientists of all skill levels to build and deploy accurate predictive models in a less time than it used to take.


Reviewers say compared to Azure Machine Learning, DataRobot is:
- Slower to reach roi
- Better at meeting requirements
Categories in common with Azure Machine Learning: [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs DataRobot](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-datarobot)
**Compare DataRobot with other alternatives:**
- [DataRobot vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/datarobot-vs-gemini-enterprise-agent-platform)
- [DataRobot vs Dataiku](https://www.g2.com/compare/datarobot-vs-dataiku)
- [DataRobot vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-datarobot)
- [DataRobot vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-datarobot)
- [DataRobot vs Alteryx](https://www.g2.com/compare/alteryx-vs-datarobot)
- [DataRobot vs IBM Watson Studio](https://www.g2.com/compare/datarobot-vs-ibm-watson-studio)
- [DataRobot vs MATLAB](https://www.g2.com/compare/datarobot-vs-matlab)
- [DataRobot vs Google Cloud AutoML](https://www.g2.com/compare/datarobot-vs-google-cloud-automl)
- [DataRobot vs Databricks](https://www.g2.com/compare/datarobot-vs-databricks)

  ### 9. [Google Cloud AutoML](https://www.g2.com/products/google-cloud-automl/reviews)
By Google
**Average Rating:** 4.1/5
**Total Reviews:** 24
Google Cloud AutoML is a suite of machine learning products designed to enable developers with limited expertise to train high-quality custom models tailored to their specific business needs. By leveraging Google's advanced transfer learning and neural architecture search technologies, AutoML simplifies the process of building, deploying, and scaling machine learning models, making AI more accessible to a broader audience. Key Features and Functionality: - Automated Model Training: AutoML automates the selection of model architecture and hyperparameter tuning, reducing the need for manual intervention and specialized knowledge. - User-Friendly Interface: The platform offers an intuitive graphical interface that allows users to upload data, train models, and manage deployments with ease. - Versatile Model Types: AutoML supports various data types and tasks through specialized services: - AutoML Vision: For image classification and object detection. - AutoML Natural Language: For text classification, sentiment analysis, and entity recognition. - AutoML Translation: For creating custom translation models between language pairs. - AutoML Video Intelligence: For video classification and object tracking. - AutoML Tables: For structured data tasks like regression and classification. - Seamless Integration: AutoML integrates with other Google Cloud services, facilitating efficient data management, model deployment, and scalability. Primary Value and Problem Solving: Google Cloud AutoML democratizes machine learning by enabling users without deep technical expertise to develop and deploy custom models. This accessibility allows businesses to harness the power of AI to solve complex problems, such as improving customer experiences through personalized recommendations, automating content moderation, enhancing language translation services, and gaining insights from large datasets. By reducing the barriers to entry, AutoML empowers organizations to innovate and stay competitive in their respective industries.


Reviewers say compared to Azure Machine Learning, Google Cloud AutoML is:
- Slower to reach roi
- Better at meeting requirements
- More usable
Categories in common with Azure Machine Learning: [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Low-Code Machine Learning Platforms](https://www.g2.com/categories/low-code-machine-learning-platforms)

**Compare:** [Azure Machine Learning vs Google Cloud AutoML](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-google-cloud-automl)
**Compare Google Cloud AutoML with other alternatives:**
- [Google Cloud AutoML vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/gemini-enterprise-agent-platform-vs-google-cloud-automl)
- [Google Cloud AutoML vs Dataiku](https://www.g2.com/compare/dataiku-vs-google-cloud-automl)
- [Google Cloud AutoML vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-google-cloud-automl)
- [Google Cloud AutoML vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-google-cloud-automl)
- [Google Cloud AutoML vs Alteryx](https://www.g2.com/compare/alteryx-vs-google-cloud-automl)
- [Google Cloud AutoML vs IBM Watson Studio](https://www.g2.com/compare/google-cloud-automl-vs-ibm-watson-studio)
- [Google Cloud AutoML vs MATLAB](https://www.g2.com/compare/google-cloud-automl-vs-matlab)
- [Google Cloud AutoML vs DataRobot](https://www.g2.com/compare/datarobot-vs-google-cloud-automl)
- [Google Cloud AutoML vs Databricks](https://www.g2.com/compare/databricks-vs-google-cloud-automl)

  ### 10. [Databricks](https://www.g2.com/products/databricks/reviews)
By Databricks Inc.
**Average Rating:** 4.6/5
**Total Reviews:** 1,343
Making big data simple


Reviewers say compared to Azure Machine Learning, Databricks is:
- Slower to reach roi
- More expensive
- Better at meeting requirements
Categories in common with Azure Machine Learning: [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [Generative AI Infrastructure](https://www.g2.com/categories/generative-ai-infrastructure)

**Compare:** [Azure Machine Learning vs Databricks](https://www.g2.com/compare/microsoft-azure-machine-learning-vs-databricks)
**Compare Databricks with other alternatives:**
- [Databricks vs Gemini Enterprise Agent Platform](https://www.g2.com/compare/databricks-vs-gemini-enterprise-agent-platform)
- [Databricks vs Dataiku](https://www.g2.com/compare/databricks-vs-dataiku)
- [Databricks vs Amazon SageMaker](https://www.g2.com/compare/amazon-sagemaker-vs-databricks)
- [Databricks vs Altair AI Studio](https://www.g2.com/compare/rapidminer-studio-vs-databricks)
- [Databricks vs Alteryx](https://www.g2.com/compare/alteryx-vs-databricks)
- [Databricks vs IBM Watson Studio](https://www.g2.com/compare/databricks-vs-ibm-watson-studio)
- [Databricks vs MATLAB](https://www.g2.com/compare/databricks-vs-matlab)
- [Databricks vs DataRobot](https://www.g2.com/compare/datarobot-vs-databricks)
- [Databricks vs Google Cloud AutoML](https://www.g2.com/compare/databricks-vs-google-cloud-automl)


---
## Azure Machine Learning Alternatives FAQs

### What features do alternatives offer that Azure Machine Learning Studio does not?

Alternatives to Azure Machine Learning Studio offer features such as integrated autonomous agent orchestration (Gemini Enterprise Agent Platform), extensive visual data lineage and hybrid code/no-code workflows (Dataiku), fully managed end-to-end ML lifecycle with automated model tuning and scalable infrastructure (Amazon SageMaker), drag-and-drop AI model building with strong AutoML and generative AI support (Altair AI Studio), unified analytics and automation with broad connectivity and scheduling (Alteryx), enterprise-grade MLOps with AutoAI and multi-language support (IBM Watson Studio), high-level numerical computing with specialized toolboxes and simulation (MATLAB), automated model selection and deployment with explainability (DataRobot), and simplified custom model training with transfer learning and human labeling (Google Cloud AutoML). Many alternatives provide easier administration, better usability, and more comprehensive integration capabilities than Azure Machine Learning Studio.



### What are the best alternatives to Azure Machine Learning Studio?

The best alternatives to Azure Machine Learning Studio include [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) (4.3/5 stars, 658 reviews), [Dataiku](https://www.g2.com/products/dataiku/reviews) (4.4/5 stars, 201 reviews), [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) (4.2/5 stars, 55 reviews), [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) (4.6/5 stars, 519 reviews), [Alteryx](https://www.g2.com/products/alteryx/reviews) (4.6/5 stars, 816 reviews), [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) (4.2/5 stars, 167 reviews), [MATLAB](https://www.g2.com/products/matlab/reviews) (4.5/5 stars, 771 reviews), [DataRobot](https://www.g2.com/products/datarobot/reviews) (4.4/5 stars, 28 reviews), [Google Cloud AutoML](https://www.g2.com/products/google-cloud-automl/reviews) (4.1/5 stars, 22 reviews), and [Databricks](https://www.g2.com/products/databricks/reviews) (4.6/5 stars, 803 reviews). These alternatives are favored for their comprehensive features, usability, and scalability.



### Which Data Science and Machine Learning Platforms tools do reviewers recommend instead of Azure Machine Learning Studio?

Reviewers recommend alternatives such as [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) for its ease of use, integrated autonomous agent workflows, and enterprise-grade governance. [Dataiku](https://www.g2.com/products/dataiku/reviews) is praised for its visual data lineage, hybrid code/no-code environment, and collaboration features. [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) is recommended for its fully managed end-to-end ML lifecycle, scalability, and integration with AWS. [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) is favored for its drag-and-drop interface and AutoML capabilities. [Alteryx](https://www.g2.com/products/alteryx/reviews) is noted for its automation and broad connectivity. [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) is valued for its AutoAI and enterprise-grade MLOps. [MATLAB](https://www.g2.com/products/matlab/reviews) is recommended for numerical computing and specialized toolboxes. [DataRobot](https://www.g2.com/products/datarobot/reviews) is appreciated for automated model building and explainability. [Google Cloud AutoML](https://www.g2.com/products/google-cloud-automl/reviews) is suggested for ease of use and transfer learning. [Databricks](https://www.g2.com/products/databricks/reviews) is endorsed for its unified data engineering, analytics, and ML platform with collaborative notebooks and Delta Lake integration.



### Why do users choose Gemini Enterprise Agent Platform over Azure Machine Learning Studio?

Users choose [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) over Azure Machine Learning Studio primarily for its extensive model variety, integrated AI capabilities, and seamless integration within the Google Cloud ecosystem. With 658 reviews highlighting ease of use (162 mentions), model variety (114 mentions), and integrated platform features (84 mentions), Gemini appeals to users seeking a comprehensive AI solution that supports multimodal inputs (text, images, code, documents) and advanced agent orchestration. Gemini's strengths include efficient automation of complex workflows, fast response times, and the ability to build and manage multiple AI agents, which save significant development time. Its generative AI APIs and evaluation tooling are particularly valued for scaling production-grade AI solutions. Users also appreciate the platform's flexibility in deploying and managing models with strong cloud service integration. Despite a noted steeper learning curve and higher pricing, users prioritize Gemini's advanced AI technology, broad model access including Gemini family models, and its unified environment for machine learning lifecycle management. These factors drive preference for Gemini when users require powerful, scalable AI solutions with rich features and deep Google Cloud integration, as reflected in G2's data with 75 mentions of expense balanced against 104 mentions of machine learning capabilities and 83 mentions of AI integration.



### How does Azure Machine Learning Studio compare to Gemini Enterprise Agent Platform?

According to G2 data, both [Azure Machine Learning Studio](https://www.g2.com/products/microsoft-azure-machine-learning/reviews) and [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) hold an equal average rating of 4.3 out of 5, with Azure having 90 reviews and Gemini 658 reviews, indicating comparable overall user satisfaction but a broader user base for Gemini. Dimension scores show Azure leads Gemini in "Better at Support" (8.6 vs 8.1, a 0.5-point difference), "Easier to Do Business With" (8.6 vs 8.3, 0.3-point difference), "Easier to Set Up" (8.3 vs 8.1, 0.2-point difference), "More Usable" (8.5 vs 8.2, 0.3-point difference), "Easier to Admin" (8.3 vs 7.9, 0.4-point difference), and "Better at Meeting Requirements" (8.5 vs 8.6, a marginal 0.1-point lead for Gemini). User reviews highlight Azure Machine Learning Studio's strengths in scalability, seamless integration with Azure services, automation, and ease of deployment, with multiple mentions of efficient model training and deployment workflows. However, users note a steep learning curve and complexity in UI navigation. Gemini Enterprise Agent Platform is praised for its ease of use, extensive model variety, integrated platform capabilities, and strong AI integration, especially with Google Cloud services. Users appreciate its multimodal capabilities and agent orchestration features but mention complexity in advanced workflow setup and higher costs. In summary, Azure Machine Learning Studio excels in support, usability, and business ease, while Gemini Enterprise Agent Platform offers a broader feature set with strong AI and cloud integration but with a steeper learning curve and higher cost concerns. Both platforms serve enterprise needs effectively but cater to slightly different user priorities and ecosystems.




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