2024-05-14 13:56:38

Azure Databricks

Fast, easy, and collaborative Apache SparkTM based analytics service


  • Company Name : Microsoft Azure



  • About Solution :

    Big data analytics and AI with optimized Apache Spark

     

    Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.

     

    Start quickly with an optimized Apache Spark environment

    Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO).

     

    Boost productivity with a shared workspace and common languages

     

    Collaborate effectively on shared projects using the interactive workspace and notebook experience, whether you’re a data engineer, data scientist, or business analyst. Build with your choice of language, including Python, Scala, R, and SQL. Get easy version control of notebooks with GitHub and Azure DevOps.

     

    Turbocharge machine learning on big data

    Access advanced automated machine learning capabilities using the integrated Azure Machine Learning to quickly identify suitable algorithms and hyperparameters. Simplify management, monitoring, and updating of machine learning models deployed from the cloud to the edge. Azure Machine Learning also provides a central registry for your experiments, machine learning pipelines, and models.

     

    Get high-performance modern data warehousing

    Combine data at any scale and get insights through analytical dashboards and operational reports. Automate data movement using Azure Data Factory, then load data into Azure Data Lake Storage, transform and clean it using Azure Databricks, and make it available for analytics using Azure Synapse Analytics. Modernize your data warehouse in the cloud for unmatched levels of performance and scalability.

     

    Key service capabilities

     

    Optimized spark engine

    Simple data processing on autoscaling infrastructure, powered by highly optimized Apache Spark™ for up to 50x performance gains.

     

    Machine learning run time

    One-click access to preconfigured machine learning environments for augmented machine learning with state-of-the-art and popular frameworks such as PyTorch, TensorFlow, and scikit-learn.

     

    MLflow

    Track and share experiments, reproduce runs, and manage models collaboratively from a central repository.

     

    Choice of language

    Use your preferred language, including Python, Scala, R, Spark SQL and .Net—whether you use serverless or provisioned compute resources.

     

    Collaborative notebooks

    Quickly access and explore data, find and share new insights, and build models collaboratively with the languages and tools of your choice.

     

    Delta lake

    Bring data reliability and scalability to your existing data lake with an open source transactional storage layer designed for the full data lifecycle.

  1. Feature 1 : Large-scale data processing for batch and streaming workloads
  2. Feature 2 : Enable analytics for the most complete and recent data
  3. Feature 3 : Simplify and accelerate data science on large datasets
  1. USP 1 : Fast, optimized Apache Spark environment
  1. Price 1 : 0.40/DBU-hour
  2. Price 2 : 0.55/DBU-hour
  1. Feedback 1 : "Azure Databricks, a scalable pass platform for data engineering and ai"
  2. Feedback 2 : "Azure Databrick as best Automation Tool for processing and transforming massive quantities of data."
  3. Feedback 3 : "Azure Databricks takes away all the pain"
  1. Story 1 : We can easily scale up and retrain our models on a continuous basis. And because Azure Databricks is highly elastic, we get really powerful spin up/spin down capabilities, and our developers love its neat, elegant user interface. Daniel Jeavons: General Manager for Data Science Shell
  2. Story 2 : With Azure Databricks and other Azure services, our resources are focused on optimizing ADAMA instead of building a platform to run it. Declan O’Halloran: Director
  3. Story 3 : Using Azure Databricks, we created a dashboard in three days that shows what was paid, owed, the gap, and payment history—and reveals patterns or trends. That would have taken three weeks to build manually. Thomas Gianniodis: General Manager IT

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