17 Integrations with Azure Data Science Virtual Machines

View a list of Azure Data Science Virtual Machines integrations and software that integrates with Azure Data Science Virtual Machines below. Compare the best Azure Data Science Virtual Machines integrations as well as features, ratings, user reviews, and pricing of software that integrates with Azure Data Science Virtual Machines. Here are the current Azure Data Science Virtual Machines integrations in 2026:

  • 1
    TensorFlow

    TensorFlow

    TensorFlow

    An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.
    Starting Price: Free
  • 2
    Microsoft 365

    Microsoft 365

    Microsoft

    Microsoft 365 for Individuals is a complete productivity suite that combines powerful applications, secure cloud storage, and AI-driven tools to help users achieve more in their daily lives. It integrates popular apps like Word, Excel, PowerPoint, Outlook, OneNote, and OneDrive, all enhanced with Copilot—Microsoft’s intelligent AI companion. The platform enables seamless collaboration, creativity, and organization across devices, including PC, Mac, iPhone, iPad, and Android. With Microsoft Designer, users can create stunning visuals, while Clipchamp adds professional-grade video editing capabilities. Built-in Microsoft Defender provides advanced security for personal data and devices. Microsoft 365 empowers individuals to imagine, create, and accomplish with greater efficiency and confidence.
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    Starting Price: $9.99/month
  • 3
    Microsoft Excel
    Microsoft Excel is the industry-standard spreadsheet application that helps users organize, analyze, and visualize data with precision and power. Whether you’re managing budgets, tracking performance, or analyzing complex datasets, Excel simplifies every task with intuitive tools and intelligent automation. With Copilot, you can now ask Excel to write formulas, summarize data, or create visualizations—all powered by AI. From basic spreadsheets to advanced financial modeling, Excel adapts to your skill level and workflow. Its cloud collaboration through Microsoft 365 lets multiple users edit, share, and comment in real time from any device. With flexible templates, built-in charts, and cross-platform integration, Excel turns numbers into insights you can act on.
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    Starting Price: $8.25 per user per month
  • 4
    Microsoft Azure
    Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it.
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    Anaconda

    Anaconda

    Anaconda

    Empowering the enterprise to do real data science at speed and scale with a full-featured machine learning platform. Spend less time managing tools and infrastructure, so you can focus on building machine learning applications that move your business forward. Anaconda Enterprise takes the headache out of ML operations, puts open-source innovation at your fingertips, and provides the foundation for serious data science and machine learning production without locking you into specific models, templates, or workflows. Software developers and data scientists can work together with AE to build, test, debug, and deploy models using their preferred languages and tools. AE provides access to both notebooks and IDEs so developers and data scientists can work together more efficiently. They can also choose from example projects and preconfigured projects. AE projects are automatically containerized so they can be moved between environments with ease.
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    Microsoft Power BI
    Power BI is a business intelligence platform that enables users to analyze data using AI-driven tools and intuitive report creation. It consolidates data from various sources into OneLake, creating a centralized data source. This platform aids in embedding actionable insights into applications like Microsoft 365, aiding decision-making. Power BI integrates with Microsoft Fabric, enhancing data management. It offers scalability to handle large data volumes and integrates seamlessly with Microsoft services. Its AI capabilities efficiently identify patterns and generate insights. Power BI ensures data security and compliance. Its Copilot feature allows rapid report generation. Additionally, Power BI Pro offers self-service analytics, and its free version includes data modeling and visualization tools. It's known for unified data management, empowering users with accessibility and training resources. Power BI has demonstrated a significant ROI and economic benefit, as evidenced in a Forres
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    Starting Price: $10 per user per month
  • 7
    Microsoft Cognitive Toolkit
    The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub.
  • 8
    SQL Server

    SQL Server

    Microsoft

    Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.
    Starting Price: Free
  • 9
    Jupyter Notebook

    Jupyter Notebook

    Project Jupyter

    The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
  • 10
    Visual Studio

    Visual Studio

    Microsoft

    Microsoft Visual Studio is the industry-leading integrated development environment (IDE) for building modern applications across desktop, mobile, cloud, and web. It empowers developers to write, refactor, debug, test, and deploy software faster with intelligent assistance powered by GitHub Copilot and AI-driven workflows. With Agent Mode, developers can automate repetitive coding tasks, optimize performance, and receive contextual help directly in the IDE. The suite includes Visual Studio 2022, the comprehensive IDE for .NET and C++ development on Windows, and Visual Studio Code, the lightweight, cross-platform editor supporting JavaScript, Python, and dozens of other languages. Visual Studio integrates seamlessly with Azure, GitHub, and CI/CD pipelines, enabling teams to collaborate and ship code efficiently. Trusted by millions worldwide, Visual Studio provides the tools and intelligence developers need to build reliable, scalable, and secure applications from concept to release.
    Starting Price: $45/user/month
  • 11
    Azure Blob Storage
    Massively scalable and secure object storage for cloud-native workloads, archives, data lakes, high-performance computing, and machine learning. Azure Blob Storage helps you create data lakes for your analytics needs, and provides storage to build powerful cloud-native and mobile apps. Optimize costs with tiered storage for your long-term data, and flexibly scale up for high-performance computing and machine learning workloads. Blob storage is built from the ground up to support the scale, security, and availability needs of mobile, web, and cloud-native application developers. Use it as a cornerstone for serverless architectures such as Azure Functions. Blob storage supports the most popular development frameworks, including Java, .NET, Python, and Node.js, and is the only cloud storage service that offers a premium, SSD-based object storage tier for low-latency and interactive scenarios.
    Starting Price: $0.00099
  • 12
    easybooking JULIA
    As a host you have to spend many hours in front of the computer answering enquiries, writing bills and managing availabilities. With JULIA, the virtual receptionist, this effort has come to an end! JULIA is more than just a hotel program: as a complete solution, it takes care of the sale of beds independently and around the clock through online bookability and channel management. JULIA facilitates room administration, guest communication, registration, accounting, and much more. Thanks to numerous interfaces to booking platforms such as booking, Airbnb, or expedia, the software simultaneously meets the requirements of guests, hosts, and small hotels. From the inquiry to the thank you email: JULIA reminds you of open offers, transmits arrival information, and issues invoices. Automatically and in up to seven languages.
    Starting Price: $220 per year
  • 13
    Azure Machine Learning
    Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.
  • 14
    Apache Spark

    Apache Spark

    Apache Software Foundation

    Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
  • 15
    VMware Cloud
    Build, run, manage, connect and protect all of your apps on any cloud. The Multi-Cloud solutions from VMware deliver a cloud operating model for all applications. Support your digital business initiatives with the world’s most proven and widely deployed cloud infrastructure. Leverage the same skills you use in the data center, while tapping into the depth and breadth of six global hyperscale public cloud providers and 4,000+ VMware Cloud Provider Partners. With hybrid cloud built on VMware Cloud Foundation, you get consistent infrastructure and operations for new and existing cloud native applications, from data center to cloud to edge. This consistency improves agility and reduces complexity, cost and risk. Build, run and manage modern apps on any cloud, meeting diverse needs with on-premises and public cloud resources. Manage both container-based workloads and traditional VM-based workloads on a single platform.
  • 16
    MLflow

    MLflow

    MLflow

    MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.
  • 17
    Azure Marketplace
    Azure Marketplace is a comprehensive online store that provides access to thousands of certified, ready-to-use software applications, services, and solutions from Microsoft and third-party vendors. It enables businesses to discover, purchase, and deploy software directly within the Azure cloud environment. The marketplace offers a wide range of products, including virtual machine images, AI and machine learning models, developer tools, security solutions, and industry-specific applications. With flexible pricing options like pay-as-you-go, free trials, and subscription models, Azure Marketplace simplifies the procurement process and centralizes billing through a single Azure invoice. It supports seamless integration with Azure services, enabling organizations to enhance their cloud infrastructure, streamline workflows, and accelerate digital transformation initiatives.
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