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Red Hat OpenShift Data Science description
Red Hat OpenShift Data Science is a cloud-based platform designed to help your team build, deploy, and manage artificial intelligence (AI) models. It provides a shared workspace and tools for data scientists to build AI models and seamlessly integrate them into applications. Red Hat OpenShift Data Science offers flexibility for deployment on your own systems or in the cloud and leverages open-source technologies for a customizable solution.
Who is Red Hat OpenShift Data Science best for
Red Hat OpenShift Data Science is a cloud service for building, deploying, and managing AI/ML models. Ideal for companies with established data science teams, it offers a collaborative environment with flexible deployment options. Users praise its performance and integrations but note a steep learning curve. Best for enterprises seeking a scalable AI/ML platform.
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Best for enterprise companies.
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Suitable for various industries.
Red Hat OpenShift Data Science features
| Supported Models can be deployed to the cloud. |
| Supported OpenShift AI supports data transformation, ingestion, and feature engineering, implying data cleaning capabilities. |
| Supported OpenShift Data Science supports GPU training via NVIDIA GPUs. |
| Supported Red Hat OpenShift AI offers tools and frameworks for building, training, and deploying AI models. |
Red Hat OpenShift Data Science reviews
We've summarised 25 Red Hat OpenShift Data Science reviews (Red Hat OpenShift Data Science G2 reviews) and summarised the main points below.
- Excellent performance and ease of use.
- Seamless integration with other tools and platforms.
- Facilitates efficient data analysis and valuable insights.
- Provides a collaborative environment for data science teams.
- Flexible deployment options (cloud, on-premise, hybrid).
- Initial learning curve can be steep for new users.
- Advanced features may require specialized technical knowledge.
- Resource intensive, especially with large datasets and multiple containers.
- Can be expensive, especially with additional services.
- Documentation can be improved, some outdated or incomplete content.
Red Hat OpenShift Data Science pricing
The commentary is based on 6 reviews from Red Hat OpenShift Data Science G2 reviews.
Red Hat OpenShift Data Science's pricing can be a concern, especially with potential extra service costs. However, some users find it cost-effective, especially given its open-source foundation and free tier for core features. It offers a valuable solution despite potential expense for smaller businesses or individuals.
Red Hat OpenShift Data Science alternatives
ClearMLOpen-source and has more momentum currently. Offers a free plan and targets a broader range of AI professionals.Read more
Qlik AutoMLBetter for those without dedicated data scientists. Has broader industry applicability. Qlik AutoML is growing faster. Lower average rating.Read more
Vertex AIBetter for users without coding experience and offers pre-trained models. Easier to use, but potentially more expensive and has less positive customer service feedback. Broader industry applicability.Read more
GeminiBetter for text and code generation. More user-friendly interface. Easier implementation. Positive pricing sentiment. Broader ideal customer profile.Read more
DataloopBetter for computer vision and unstructured data annotation. Has pre-built models and pipelines for faster AI development. More user-friendly interface but suffers from occasional performance issues and bugs. Is growing faster in website traffic but has declining employee growth.Read more
SAS Visual Data Mining and Machine LearningBetter suited for users with varying technical skills due to its intuitive visual interface. Offers broader industry fit, including healthcare and pharmaceuticals. Has significantly more momentum based on employee growth. However, it has limitations in model creation options and open-source integration. It can also be expensive, particularly compared to open-source alternatives.Read more
Red Hat OpenShift Data Science FAQ
What is Red Hat OpenShift Data Science and what does Red Hat OpenShift Data Science do?
Red Hat OpenShift Data Science is a cloud-based platform for building, deploying, and managing AI/ML models. It provides a shared workspace and tools for data scientists, enabling them to develop models and integrate them into applications. It offers flexible deployment options and utilizes open-source technologies.
How does Red Hat OpenShift Data Science integrate with other tools?
Red Hat OpenShift Data Science seamlessly integrates with various tools and platforms, facilitating efficient data analysis and model deployment. It leverages open-source technologies, offering flexibility and customization for diverse data science workflows. This streamlines development and promotes valuable insights.
What the main competitors of Red Hat OpenShift Data Science?
Top alternatives to Red Hat OpenShift Data Science include Qlik AutoML, ClearML, SAS Visual Data Mining and Machine Learning, and SAS Viya. These platforms offer similar data science capabilities for building, deploying, and managing AI/ML models.
Is Red Hat OpenShift Data Science legit?
Yes, Red Hat OpenShift Data Science is a legitimate product from Red Hat. It's a secure and reliable platform used by various companies for building, deploying, and managing AI/ML models. It offers seamless integration, flexible deployment, and robust performance, though it has a learning curve.
How much does Red Hat OpenShift Data Science cost?
I cannot find pricing information for Red Hat OpenShift Data Science. Contact Red Hat sales for product pricing details if you are considering this data science platform.
Is Red Hat OpenShift Data Science customer service good?
Customer reviews indicate that Red Hat OpenShift Data Science provides excellent performance and helpful support. However, some users mention that the documentation and technical support could be improved.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.