Compare the Top Data Science Software that integrates with Hugging Face as of October 2025

This a list of Data Science software that integrates with Hugging Face. Use the filters on the left to add additional filters for products that have integrations with Hugging Face. View the products that work with Hugging Face in the table below.

What is Data Science Software for Hugging Face?

Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends. Compare and read user reviews of the best Data Science software for Hugging Face currently available using the table below. This list is updated regularly.

  • 1
    Teradata VantageCloud
    Teradata VantageCloud: The complete cloud analytics and data platform for AI. VantageCloud is the complete cloud analytics and data platform, delivering harmonized data and Trusted AI for all. Built for performance, flexibility, and openness, VantageCloud enables organizations to unify diverse data sources, run complex analytics, and deploy AI models—all within a single, scalable platform. With support for multi-cloud and hybrid deployments, VantageCloud empowers businesses to manage data across public clouds and on-premises environments. Its open data architecture ensures compatibility with industry-standard formats, preventing vendor lock-in and enabling seamless integration with modern data solutions. VantageCloud gives organizations the tools and confidence to unlock the hidden insights in data, power infinite innovation, and reveal new opportunities.
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  • 2
    Dataiku

    Dataiku

    Dataiku

    Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries.
  • 3
    TrueFoundry

    TrueFoundry

    TrueFoundry

    TrueFoundry is a Cloud-native Machine Learning Training and Deployment PaaS on top of Kubernetes that enables Machine learning teams to train and Deploy models at the speed of Big Tech with 100% reliability and scalability - allowing them to save cost and release Models to production faster. We abstract out the Kubernetes for Data Scientists and enable them to operate in a way they are comfortable. It also allows teams to deploy and fine-tune large language models seamlessly with full security and cost optimization. TrueFoundry is open-ended, API Driven and integrates with the internal systems, deploys on a company's internal infrastructure and ensures complete Data Privacy and DevSecOps practices.
    Starting Price: $5 per month
  • 4
    Amazon SageMaker Unified Studio
    Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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