Top 10 Amazon SageMaker Alternatives & Competitors

(48)4.2 out of 5

Research alternative solutions to Amazon SageMaker on G2, with real user reviews on competing tools. Data Science and Machine Learning Platforms is a widely used technology, and many people are seeking reliable, user friendly software solutions with drag and drop, pre-built algorithms, and model training. Other important factors to consider when researching alternatives to Amazon SageMaker include reliability and ease of use. The best overall Amazon SageMaker alternative is Vertex AI. Other similar apps like Amazon SageMaker are Dataiku, Azure Machine Learning, Alteryx, and IBM Watson Studio. Amazon SageMaker alternatives can be found in Data Science and Machine Learning Platforms but may also be in Generative AI Infrastructure Software or Analytics Platforms.

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Best Paid & Free Alternatives to Amazon SageMaker

Vertex AI
Dataiku
Azure Machine Learning
Alteryx
IBM Watson Studio
Altair AI Studio
DataRobot
H2O

Top 10 Alternatives to Amazon SageMaker Recently Reviewed By G2 Community

Browse options below. Based on reviewer data, you can see how Amazon SageMaker stacks up to the competition, check reviews from current & previous users in industries like Information Technology and Services, Higher Education, and Internet, and find the best product for your business.

Vertex AI

By Google

4.3/5

(626)

Product Description

Vertex AI 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. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. 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. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI 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 Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.

Categories in common with Amazon SageMaker:

MLOps Platforms

Data Science and Machine Learning Platforms

Generative AI Infrastructure

Low-Code Machine Learning Platforms

Dataiku

By Dataiku

4.4/5

(188)

Product Description

Reviewers say compared to Amazon SageMaker, Dataiku is:

More usable

More expensive

Better at meeting requirements

Categories in common with Amazon SageMaker:

MLOps Platforms

Data Science and Machine Learning Platforms

Generative AI Infrastructure

Low-Code Machine Learning Platforms

Azure Machine Learning

By Microsoft

4.3/5

(88)

Product Description

Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces. - AI Infrastructure: Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking. - Automated Machine Learning: Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing. - Responsible AI: Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness. - Model Catalog: Discover, fine-tune, and deploy foundation models from Microsoft, OpenAI, Hugging Face, Meta, Cohere, and more using the model catalog. - Prompt Flow: Design, construct, evaluate, and deploy language model workflows with prompt flow. - Managed Endpoints: Operationalize model deployment and scoring, log metrics, and perform safe model rollouts. Primary Value and Solutions Provided: Azure Machine Learning accelerates time to value by streamlining prompt engineering and machine learning model workflows, facilitating faster model development with powerful AI infrastructure. It streamlines operations by enabling reproducible end-to-end pipelines and automating workflows with continuous integration and continuous delivery (CI/CD). The platform ensures confidence in development through unified data and AI governance with built-in security and compliance, allowing compute to run anywhere for hybrid machine learning. Additionally, it promotes responsible AI by providing visibility into models, evaluating language model workflows, and mitigating fairness, biases, and harm with built-in safety systems.

Reviewers say compared to Amazon SageMaker, Azure Machine Learning is:

More usable

Better at support

Categories in common with Amazon SageMaker:

MLOps Platforms

Data Science and Machine Learning Platforms

Generative AI Infrastructure

Low-Code Machine Learning Platforms

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IBM Watson Studio

By IBM

4.2/5

(165)

Product Description

Reviewers say compared to Amazon SageMaker, IBM Watson Studio is:

Slower to reach roi

Categories in common with Amazon SageMaker:

MLOps Platforms

Data Science and Machine Learning Platforms

Altair AI Studio

By Altair

4.6/5

(509)

Product Description

Reviewers say compared to Amazon SageMaker, Altair AI Studio is:

Easier to set up

More usable

Better at meeting requirements

Categories in common with Amazon SageMaker:

Data Science and Machine Learning Platforms

Generative AI Infrastructure

Low-Code Machine Learning Platforms

DataRobot

By DataRobot

4.4/5

(26)

Product Description

Reviewers say compared to Amazon SageMaker, DataRobot is:

Better at meeting requirements

More usable

Categories in common with Amazon SageMaker:

Data Science and Machine Learning Platforms

Low-Code Machine Learning Platforms

H2O

By H2O.ai

4.5/5

(24)

Product Description

Reviewers say compared to Amazon SageMaker, H2O is:

More usable

Better at support

Categories in common with Amazon SageMaker:

Data Science and Machine Learning Platforms

Generative AI Infrastructure

Google Cloud AutoML

By Google

4.1/5

(22)

Product Description

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 Amazon SageMaker, Google Cloud AutoML is:

More usable

Categories in common with Amazon SageMaker:

Data Science and Machine Learning Platforms

Low-Code Machine Learning Platforms