# Amazon SageMaker vs Google Cloud AutoML Comparison | | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Star Rating** | 4.2 out of 5 | 4.1 out of 5 | | **Total Reviews** | 48 | 22 | | **Largest Market Segment** | Enterprise (34.9% of reviews) | Small-Business (45.5% of reviews) | | **Entry Level Price** | No pricing available | No pricing available | --- ## Top Pros & Cons ### Amazon SageMaker Pros: - Ease of Use (3 reviews) - AI Integration (2 reviews) Cons: - Expensive (3 reviews) - Complexity (2 reviews) ### Google Cloud AutoML Pros: - AI Integration (1 reviews) - Ease of Use (1 reviews) Cons: - Cost (1 reviews) - Expensive (1 reviews) --- ## Ratings Comparison | Rating | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Meets Requirements** | 8.6 (38 reviews) | 8.6 (14 reviews) | | **Ease of Use** | 8.4 (39 reviews) | 8.6 (14 reviews) | | **Ease of Setup** | 8.5 (26 reviews) | 7.4 (11 reviews) | | **Ease of Admin** | 8.4 (20 reviews) | 7.9 (12 reviews) | | **Quality of Support** | 8.6 (34 reviews) | 7.5 (14 reviews) | | **Has the product been a good partner in doing business?** | 9.2 (20 reviews) | 8.3 (11 reviews) | | **Product Direction (% positive)** | 9.1 (37 reviews) | 8.9 (11 reviews) | --- ## Pricing ### Amazon SageMaker #### Entry-Level Pricing No pricing available #### Free Trial No information available ### Google Cloud AutoML #### Entry-Level Pricing No pricing available #### Free Trial No information available --- ## Features Comparison By Category ### MLOps Platforms | Product | Score | Reviews | |---|---|---| | **Amazon SageMaker** | N/A | N/A | | **Google Cloud AutoML** | N/A | N/A | #### Deployment | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Language Flexibility** | Not enough data | Not enough data | | **Framework Flexibility** | Not enough data | Not enough data | | **Versioning** | Not enough data | Not enough data | | **Ease of Deployment** | Not enough data | Not enough data | | **Scalability** | Not enough data | Not enough data | #### Deployment | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Language Flexibility** | Not enough data | Not enough data | | **Framework Flexibility** | Not enough data | Not enough data | | **Versioning** | Not enough data | Not enough data | | **Ease of Deployment** | Not enough data | Not enough data | | **Scalability** | Not enough data | Not enough data | #### Management | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Cataloging** | Not enough data | Not enough data | | **Monitoring** | Not enough data | Not enough data | | **Governing** | Not enough data | Not enough data | | **Model Registry** | Not enough data | Not enough data | #### Operations | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Metrics** | Not enough data | Not enough data | | **Infrastructure management** | Not enough data | Not enough data | | **Collaboration** | Not enough data | Not enough data | #### Management | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Cataloging** | Not enough data | Not enough data | | **Monitoring** | Not enough data | Not enough data | | **Governing** | Not enough data | Not enough data | #### Generative AI | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI Text Generation** | Not enough data | Not enough data | | **AI Text Summarization** | Not enough data | Not enough data | ### Data Science and Machine Learning Platforms | Product | Score | Reviews | |---|---|---| | **Amazon SageMaker** | 8.8/10 | 37 | | **Google Cloud AutoML** | N/A | N/A | #### System | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Data Ingestion & Wrangling** | 8.3 (20 reviews) | Not enough data | #### Model Development | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Language Support** | 8.7 (29 reviews) | Not enough data | | **Drag and Drop** | 8.2 (28 reviews) | Not enough data | | **Pre-Built Algorithms** | 8.3 (33 reviews) | Not enough data | | **Model Training** | 8.9 (33 reviews) | Not enough data | #### Model Development | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Feature Engineering** | 8.4 (19 reviews) | Not enough data | #### Machine/Deep Learning Services | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Computer Vision** | 8.9 (26 reviews) | Not enough data | | **Natural Language Processing** | 9.1 (28 reviews) | Not enough data | | **Natural Language Generation** | 8.9 (25 reviews) | Not enough data | | **Artificial Neural Networks** | 9.0 (28 reviews) | Not enough data | #### Machine/Deep Learning Services | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Natural Language Understanding** | 9.2 (17 reviews) | Not enough data | | **Deep Learning** | 9.2 (18 reviews) | Not enough data | #### Deployment | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Managed Service** | 8.7 (33 reviews) | Not enough data | | **Application** | 8.7 (33 reviews) | Not enough data | | **Scalability** | 9.0 (31 reviews) | Not enough data | #### Generative AI | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI Text Generation** | 8.6 (6 reviews) | Not enough data | | **AI Text Summarization** | 9.2 (6 reviews) | Not enough data | | **AI Text-to-Image** | 8.3 (5 reviews) | Not enough data | #### Agentic AI - Data Science and Machine Learning Platforms | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Autonomous Task Execution** | Not enough data | Not enough data | | **Multi-step Planning** | Not enough data | Not enough data | | **Cross-system Integration** | Not enough data | Not enough data | | **Adaptive Learning** | Not enough data | Not enough data | | **Natural Language Interaction** | Not enough data | Not enough data | | **Proactive Assistance** | Not enough data | Not enough data | | **Decision Making** | Not enough data | Not enough data | ### Generative AI Infrastructure | Product | Score | Reviews | |---|---|---| | **Amazon SageMaker** | N/A | N/A | | **Google Cloud AutoML** | N/A | N/A | #### Scalability and Performance - Generative AI Infrastructure | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI High Availability** | Not enough data | Not enough data | | **AI Model Training Scalability** | Not enough data | Not enough data | | **AI Inference Speed** | Not enough data | Not enough data | #### Cost and Efficiency - Generative AI Infrastructure | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI Cost per API Call** | Not enough data | Not enough data | | **AI Resource Allocation Flexibility** | Not enough data | Not enough data | | **AI Energy Efficiency** | Not enough data | Not enough data | #### Integration and Extensibility - Generative AI Infrastructure | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI Multi-cloud Support** | Not enough data | Not enough data | | **AI Data Pipeline Integration** | Not enough data | Not enough data | | **AI API Support and Flexibility** | Not enough data | Not enough data | #### Security and Compliance - Generative AI Infrastructure | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI GDPR and Regulatory Compliance** | Not enough data | Not enough data | | **AI Role-based Access Control** | Not enough data | Not enough data | | **AI Data Encryption** | Not enough data | Not enough data | #### Usability and Support - Generative AI Infrastructure | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **AI Documentation Quality** | Not enough data | Not enough data | | **AI Community Activity** | Not enough data | Not enough data | ### Low-Code Machine Learning Platforms | Product | Score | Reviews | |---|---|---| | **Amazon SageMaker** | N/A | N/A | | **Google Cloud AutoML** | N/A | N/A | #### Data Ingestion & Preparation - Low-Code Machine Learning Platforms | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Automatic Data Profiling & Quality Assessment** | Not enough data | Not enough data | | **Multi‑Source Connector Support** | Not enough data | Not enough data | | **Schema Drift / Change Detection** | Not enough data | Not enough data | #### Model Construction & Automation - Low-Code Machine Learning Platforms | Feature | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Guided Algorithm & Hyperparameter Recommendation** | Not enough data | Not enough data | | **Code Extensibility** | Not enough data | Not enough data | | **Automated Feature Engineering** | Not enough data | Not enough data | --- ## Categories **Shared Categories (2):** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [ Low-Code Machine Learning Platforms Software](https://www.g2.com/categories/low-code-machine-learning-platforms) **Unique to Amazon SageMaker (2):** [MLOps Platforms](https://www.g2.com/categories/mlops-platforms), [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) --- ## Reviewer Demographics ### By Company Size | Segment | Amazon SageMaker | Google Cloud AutoML | |---|---|---| | **Small-Business** | 32.6% | 45.5% | | **Mid-Market** | 32.6% | 27.3% | | **Enterprise** | 34.9% | 27.3% | ### By Industry #### Amazon SageMaker - **Information Technology and Services:** 20.9% - **Computer Software:** 16.3% - **Marketing and Advertising:** 4.7% - **Internet:** 4.7% - **Education Management:** 4.7% - **Hospital & Health Care:** 4.7% - **Higher Education:** 4.7% - **Financial Services:** 4.7% - **Banking:** 2.3% - **Computer & Network Security:** 2.3% - **Other:** 30.2% #### Google Cloud AutoML - **Research:** 13.6% - **Information Technology and Services:** 13.6% - **Computer Software:** 9.1% - **Accounting:** 4.5% - **Consumer Goods:** 4.5% - **Defense & Space:** 4.5% - **Education Management:** 4.5% - **Entertainment:** 4.5% - **Furniture:** 4.5% - **Higher Education:** 4.5% - **Other:** 31.8% --- ## Alternatives ### Alternatives to Amazon SageMaker - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) — 4.3/5 stars (655 reviews) - [Dataiku](https://www.g2.com/products/dataiku/reviews) — 4.4/5 stars (196 reviews) - [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews) — 4.3/5 stars (88 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) — 4.6/5 stars (727 reviews) - [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) — 4.2/5 stars (167 reviews) - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) — 4.6/5 stars (516 reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) — 4.6/5 stars (770 reviews) - [DataRobot](https://www.g2.com/products/datarobot/reviews) — 4.4/5 stars (27 reviews) - [H2O](https://www.g2.com/products/h2o/reviews) — 4.5/5 stars (24 reviews) - [Posit](https://www.g2.com/products/posit-posit/reviews) — 4.5/5 stars (570 reviews) ### Alternatives to Google Cloud AutoML - [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews) — 4.3/5 stars (88 reviews) - [DataRobot](https://www.g2.com/products/datarobot/reviews) — 4.4/5 stars (27 reviews) - [Dataiku](https://www.g2.com/products/dataiku/reviews) — 4.4/5 stars (196 reviews) - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) — 4.6/5 stars (516 reviews) - [TensorFlow](https://www.g2.com/products/tensorflow/reviews) — 4.5/5 stars (138 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) — 4.6/5 stars (727 reviews) - [H2O](https://www.g2.com/products/h2o/reviews) — 4.5/5 stars (24 reviews) - [MATLAB](https://www.g2.com/products/matlab/reviews) — 4.5/5 stars (770 reviews) - [SAS Enterprise Miner](https://www.g2.com/products/sas-enterprise-miner/reviews) — 4.2/5 stars (193 reviews) - [BigML](https://www.g2.com/products/bigml/reviews) — 4.7/5 stars (24 reviews) --- ## Top Discussions ### Amazon SageMaker - Title: [What is the best way to integrate Sagemaker models with Kubernetes?](https://www.g2.com/discussions/28784-what-is-the-best-way-to-integrate-sagemaker-models-with-kubernetes) — 1 comment > **Top comment:** "https://aws.amazon.com/blogs/machine-learning/introducing-amazon-sagemaker-operators-for-kubernetes/" - Title: [How do i make this platform reach to most of my developers?](https://www.g2.com/discussions/27976-how-do-i-make-this-platform-reach-to-most-of-my-developers) — 1 comment > **Top comment:** "you can manage the access via IAM users and roles and give them access as per their need, Sagemaker by default has all the basic AWS feature and you can..." ### Google Cloud AutoML No discussions available for this product. --- **Source:** [G2.com](https://www.g2.com) | [Comparison Page](https://www.g2.com/compare/amazon-sagemaker-vs-google-cloud-automl)