--- title: Amazon SageMaker Reviews meta_title: 'Amazon SageMaker Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 56 reviews by the users' company size, role or industry to find out how Amazon SageMaker works for a business like yours. aggregate_rating: rating_value: 4.3 review_count: 56 scale: '5' date_modified: '2026-07-13' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # Amazon SageMaker Reviews **Vendor:** Amazon Web Services (AWS) **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.3/5.0 **Total Reviews:** 56 ## About Amazon SageMaker 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. ## Amazon SageMaker Pros & Cons **What users like:** - Users find Amazon SageMaker's **ease of use** exceptional, enabling quick adaptation and efficient model training from the start. (3 reviews) - Users value the **seamless AI integration** of Amazon SageMaker, which simplifies the entire machine learning lifecycle efficiently. (2 reviews) - Users love the **impressive computing power** of Amazon SageMaker, drastically reducing model training time to minutes. (2 reviews) - Users highlight the **efficiency** of Amazon SageMaker, significantly reducing model training time and simplifying experimentation. (2 reviews) - Users enjoy the **fast processing** of Amazon SageMaker, significantly reducing model training time for efficient experimentation. (2 reviews) - Users value the **comprehensive managed Jupyter notebooks** and seamless integration with popular ML frameworks and tools. (2 reviews) - Implementation Ease (2 reviews) - Model Management (2 reviews) - Setup Ease (2 reviews) - Time-saving (2 reviews) **What users dislike:** - Users find Amazon SageMaker to be **expensive and complex** , particularly for long-running jobs and large deployments. (3 reviews) - Users find the **complex pricing structure** of Amazon SageMaker challenging, often leading to unexpected high costs. (2 reviews) - Users find the **complex pricing structure** of Amazon SageMaker can lead to unexpected costs and confusion. (2 reviews) - Users find the **steep learning curve** of Amazon SageMaker challenging, particularly for those new to AWS services. (2 reviews) - Users experience a **difficult learning curve** during the initial setup of Amazon SageMaker, impacting usability. (1 reviews) - Users find the **difficult setup** of Amazon SageMaker challenging, impacting their overall experience and cost estimation. (1 reviews) - Integration Difficulty (1 reviews) - Performance Issues (1 reviews) - Steep Learning Curve (1 reviews) ## Amazon SageMaker Reviews ### 1. Remove the barries to machine learning **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Internet | Small-Business (50 or fewer emp.) **Reviewed Date:** August 22, 2018 **What do you like best about Amazon SageMaker?** it has a lot of tools to help with training, and deploying ML models. They manage all the training techniques and the tunning of the models. So you can focus on getting something in production faster. They support many different algorithms and there is always the option to use a personal preference using docker. **What do you dislike about Amazon SageMaker?** Not much information about it online and the prices can prevent developers from using it. **Recommendations to others considering Amazon SageMaker:** If you are a company think on how much are you expecting of making after using this technology. It can become expensive quickly unless you know what you are doing. **What problems is Amazon SageMaker solving and how is that benefiting you?** This is pretty much new for us. So it is basically testing and checking the things that can be done using this technology. ### 2. Aws sagemaker review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Sporting Goods | Small-Business (50 or fewer emp.) **Reviewed Date:** September 09, 2018 **What do you like best about Amazon SageMaker?** I loved that I could upload all my data to S3 and then train my model from there. Also, the algorithms provided were very useful **What do you dislike about Amazon SageMaker?** Not much to dislike other than the fact that AWS lacked the region that is closer to me. **Recommendations to others considering Amazon SageMaker:** Would recommend cloud computation **What problems is Amazon SageMaker solving and how is that benefiting you?** It solves the need for in house training as all the computation can be done online. ### 3. Good Software ! **Rating:** 5.0/5.0 stars **Reviewed by:** Victoria P. | Web Developer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** August 19, 2018 **What do you like best about Amazon SageMaker?** It offers simple and effective personalization which simple to modify and alter. It integrates all the very best pieces of numerous programs in a user interface that is easy to use. **What do you dislike about Amazon SageMaker?** There ought to be some choices making this mobile friendly. For novices who want to utilize this platform the only drawback is that it needs high payments. **What problems is Amazon SageMaker solving and how is that benefiting you?** Amazon SageMaker provides me much easier access to other recognized knowing structures. ### 4. Open source AWS that is clean and accessible **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** June 18, 2018 **What do you like best about Amazon SageMaker?** It incorporates all of the best pieces of multiple programs in an interface that is user friendly. It includes examples and walkthroughs on how to use the different features so you can learn through usage. **What do you dislike about Amazon SageMaker?** I don't like that it is run by amazon, and not a more reliable developer. This is nearly made up for by it being open source though **What problems is Amazon SageMaker solving and how is that benefiting you?** Instead of needing to log in through multiple cloud storage programs downloading applications throughout our system, we are able to access the entirety of the information and functions that we need to work as a company. ### 5. Visit the site weekly and helps fulfill my clients requests **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** September 12, 2018 **What do you like best about Amazon SageMaker?** How easy it is to use. Tech Support is a big help when needed **What do you dislike about Amazon SageMaker?** Sometimes it breaks down and we need to open a case with Tech Support. **What problems is Amazon SageMaker solving and how is that benefiting you?** Fulfilling requests ### 6. Wonderful world of Amazon SageMaker **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Construction | Small-Business (50 or fewer emp.) **Reviewed Date:** May 04, 2018 **What do you like best about Amazon SageMaker?** Incredibly efficient program. From project conception to construction documents, sagemaker streamlines the process. Many features save days if not weeks of time. **What do you dislike about Amazon SageMaker?** At times sagemaker can be overly formulaic. This shackles creativity to some degree. The interface can at times be anything but intuitive, which leads to a long and arduous learning curve. **What problems is Amazon SageMaker solving and how is that benefiting you?** At the moment, sagemaker is the best product out there for comprehensive design, consultant collaboration, and production. ## Amazon SageMaker Discussions - [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 - [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 - [View Amazon SageMaker pricing details and edition comparison](https://www.g2.com/products/amazon-sagemaker/reviews?page=2§ion=pricing&secure%5Bexpires_at%5D=2026-07-14+13%3A22%3A45+-0500&secure%5Bsession_id%5D=67f99838-ee2a-4110-83ae-f7f197d2b9df&secure%5Btoken%5D=24c19662ba402107cd47892edcb104eae05a04f7bc881cadf2ca0010832ff26b&format=llm_user) ## Amazon SageMaker Integrations - [Amazon S3 Glacier](https://www.g2.com/products/amazon-s3-glacier/reviews) - [AWS Amplify](https://www.g2.com/products/aws-amplify/reviews) - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) - [GitLab](https://www.g2.com/products/gitlab/reviews) ## Amazon SageMaker Features **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **System** - Data Ingestion & Wrangling **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Data Ingestion & Preparation - Low-Code Machine Learning Platforms** - Automatic Data Profiling & Quality Assessment - Multi‑Source Connector Support - Schema Drift / Change Detection **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Operations** - Metrics - Infrastructure management - Collaboration **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Model Construction & Automation - Low-Code Machine Learning Platforms** - Guided Algorithm & Hyperparameter Recommendation - Code Extensibility - Automated Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Management** - Cataloging - Monitoring - Governing **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top Amazon SageMaker Alternatives - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (653 reviews) - [Dataiku](https://www.g2.com/products/dataiku/reviews) - 4.4/5.0 (210 reviews) - [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews) - 4.3/5.0 (87 reviews)