Azure Data Factory Documentation

Note that:. Azure Data Catalog. Enter Azure Data Factory 2. Yesterday at TechEd Europe 2014, Microsoft announced the preview of Azure Data Factory. Microsoft is radically simplifying cloud dev and ops in first-of-its-kind Azure Preview portal at portal. Step 1: Create Storage account and a container in Azure. Azure Data Lake store - The Data Lake store provides a single repository where organizations upload data of just about infinite volume. Choosing the right approach to Azure data ingest. Please contact its maintainers for support. Documentation. There is good documentation on Microsoft Docs to help you get started with Azure Data Factory (ADF), but there is quite a bit to learn, especially if you are getting into ADF from an Integration Services (SSIS) background. Snowflake, the data warehouse built for the cloud, is now generally available on Microsoft Azure Government. Azure Data Factory - Iterate over a data collection using Lookup and ForEach Activities - Duration: 36:07. Azure Data Factory v2 (ADF) has a new feature in public preview called Data Flow. These services and processes have been developed and enhanced while dealing with over 1,200 funds and 1,100,000 former members since 2004. you want to load data to different locations in Blob. This is similar to another on premise ETL tool, SQL Server Integration Service (SSIS), provided by Microsoft. Azure Data Factory factories are designed with a series of fairly simple JSON documents and uploaded to Azure using either the web interface, PowerShell,. All the queries I have seen in documentation are simple, single table queries with no joins. Source data can be pulled from on premise or cloud environments consisting of structured, unstructured or semi-structured data. The Apache Hive ™ data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Azure Data Factory. Microsoft is working on a service that will allow Azure users to take advantage of more analytics and data services. The C# (Reference Guide) What's New in Azure Data Factory Version 2 (ADFv2) Community Speaking Analysis with Power BI; Chaining Azure Data Factory Activities and Datasets; Azure Business Intelligence - The Icon Game! Connecting PowerBI. Azure Automation. There are a few different options for getting data into ADLS. If you have. (2019-Feb-18) With Azure Data Factory (ADF) continuous integration, you help your team to collaborate and develop data transformation solutions within the same data factory workspace and maintain your combined development efforts in a central code repository. You can use these steps to load the files with the order processing data from Azure Blob Storage. About 3 weeks ago I presented a free webinar for Pragmatic Works where I talked about Azure Data Factory V2. Agile Analytics Analytics azure azure data factory Big Data Big Data Analytics Big Data Use Cases Business Intelligence Cloud Computing Columnar Database Databases Data Visualization data warehouse ELT etl Hadoop In-memory database Machine Learning NoSQL Pentaho sql server Uncategorized Use Cases Visualization. The Data Science VM can readily leverage these services in Azure to support the deployment of large scale enterprise team -based Data Science and AI environments. Azure Data Factory helps with extracting data from multiple Azure services and persist the data as load files in Blob Storage. Data Factory enables you to process on-premises data like SQL Ser. SSIS has been. Is it possible to use Azure Data Factory to get data from a REST API and insert it to a Azure database table?. Changing this forces a new resource. Usually the very first step is creating Linked Services. Azure Data Factory is a hybrid data integration service that allows you to create, schedule and orchestrate your ETL/ELT workflows at scale wherever your data lives, in cloud or self-hosted network. Azure Data Factory allows data to move from a multitude of sources to a multitude of destinations. Read/write of entities in Azure Data Factory* Monitoring $-per 50,000 run records retrieved: Monitoring of pipeline, activity, trigger, and debug runs** * Read/write operations for Azure Data Factory entities include create, read, update, and delete. Does the Azure Data Explorer optimize the entire query if your base table access is in a function? Kusto documentation. We had an opportunity to get peek at these in private preview. That will open a separate tab for the Azure Data Factory UI. See the Azure Cosmos DB Spark Connector project for detailed documentation. Original Data Data Load Transformed Transform BI Tools Ingest (EL) Apps Original Data Scale-out Storage & Compute (HDFS, Blob Storage, etc) Transform & Load Data Marts Data Lake(s) Dashboards Streaming data. From there, you can use CrateDB (hosted on Microsoft Azure) to query and analyze the data in real-time. Azure Data Factory automatically created the column headers Prop_0 and Prop_1 for my first and last name columns. When you build out a pipeline using Azure Data Factory you will have to associate it to a storage account. DW Sentry accelerates Azure SQL Data Warehouse performance. Linked Services are connection to data sources and destinations. This includes tests against mocked storage, which is an in-memory emulation of Azure Data Lake Storage. Microsoft is radically simplifying cloud dev and ops in first-of-its-kind Azure Preview portal at portal. What's more, ADF-DF can be considered as a firm Azure equivalent for our on premises SSIS package data flow engine. Linked Services are connection to data sources and destinations. Enter Azure Data Factory 2. Have a data factory that is pulling from on prem SQL server to Azure table storage. You may also use Power BI in your job, but you are not primarily a business user. By Prasad Kona Organizations have been increasingly moving towards and adopting cloud data and cloud analytics platforms like Microsoft Azure. At Microsoft, with the announcement of v2 of the Azure Data Factory service (ADF) preview service, we've invested in expanding the data integration service in Azure to enable a series of new use cases that we found to be very popular and very common in cloud-first ETL and data integration scenarios. Does the Azure Data Explorer optimize the entire query if your base table access is in a function? Kusto documentation. The Azure Data Studio notebook viewer uses the open source Jupyter server and file format, but adds in the modern, keyboard-focused coding environment and rich editor experience of Azure Data. It has connectors for more than 70 different data services, features an easy-to-use drag-and-drop interface, supports multiple programming languages and is highly scalable. Tutorials and other documentation show you how to set up and manage data pipelines, and how to move and transform data for analysis. Azure Data Factory V2 is the data integration platform that goes beyond Azure Data Factory V1's orchestration and batch-processing of time-series data, with a general purpose app model supporting modern data warehousing patterns and scenarios, lift-and-shift SSIS, and data-driven SaaS applications. Deploy in minutes using your Azure subscription and customize as needed. DataFactories --version 4. The store is designed for high-performance processing and analytics from HDFS applications and tools, including support for low latency workloads. If the data is already in an HDFS (Hadoop Distributed File System) store, you can use tools like Sqoop or DistCp. Azure Data Factory 2. About Config Azure Latest News. Develop more efficiently with Functions, an event-driven serverless compute platform that can also solve complex orchestration problems. The ACL (access control list) grants permissions to to create, read, and/or modify files and folders stored in the ADLS service. Is Data Factory SSIS in the cloud?. Yesterday at TechEd Europe 2014, Microsoft announced the preview of Azure Data Factory. On the other hand, if you are already using Azure Data Factory, you most likely have a title like Data Engineer, ETL Developer, Data Integrator, Business Intelligence Consultant, or something similar. Azure Data Factory is a fully managed cloud-based data integration service enabling source data to be extracted, loaded and transformed (ELT) to a destination. No account? Create one! Can't access your account? Sign-in options ©2019. Azure Data Factory helps with extracting data from multiple Azure services and persist the data as load files in Blob Storage. In Azure Data Factory you can get data from a dataset by using copy activity in a pipeline. Azure Data Factory has built-in support for pipeline monitoring via Azure Monitor, API, PowerShell, Azure Monitor logs, and health panels on the Azure portal. Datasets represent data structures within the data store that is being referenced by the Linked Service object. In this first in a series of Azure Data Platform blog posts, I'll get you on your way to making your adoption of the cloud platforms and data integration easier. Acquia Cloud Site Factory. A selection of tests can run against the Azure Data Lake Storage. It feels like these two services have been around forever. In this follow-up I answer all the important questions that were posted to the Q&A pannel, like those related to the return of fun facts. 0 takes data integration to the next level and comes with a variety of triggers, integration with SSIS on-prem & in Azure, integration with Azure Monitor, control flow branching and. paket add Microsoft. With the event calendar and intelligent movement dashboard, you always know what factors are impacting workload. Azure Data Factory (ADF) is a fully managed cloud service for data orchestration and data integration. So says the Azure Quickstart Templates page. Azure Data Factory 2. Data Factory V2 was announced at Ignite 2017 and brought with it a host of new capabilities: Lift your SSIS workloads into Data Factory and run using the new Integrated Runtime (IR) Ability to schedule Data Factory using wall-clock timers or on-demand via event generation Introducing the first proper separation of Control Flow and Data Flow…. The pricing is broken down into four ways that you're paying for this service. There is quite a bit more to know about ADLS security than what is covered in this series, so be sure to also dive into the official documentation links: Security in Azure Data Lake Store. In previous post you’ve seen how to create Azure Data Factory. Have a data factory that is pulling from on prem SQL server to Azure table storage. There is good documentation on Microsoft Docs to help you get started with Azure Data Factory (ADF), but there is quite a bit to learn, especially if you are getting into ADF from an Integration Services (SSIS) background. Original Data Data Load Transformed Transform BI Tools Ingest (EL) Apps Original Data Scale-out Storage & Compute (HDFS, Blob Storage, etc) Transform & Load Data Marts Data Lake(s) Dashboards Streaming data. the web and odata connectors need to add support for OAuth ASAP. ADF is great and by running tasks in parallel not only can you run different activities but you can also run multiple date slices when you set the concurrency of the activity. The Integration Runtime is a customer managed data integration infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments. Another case is that some activities should be repeated many times, but in slightly different contexts, e. com, which provides introductory material, information about Azure account management, and end-to-end tutorials. However, Azure Data Factory V2 has finally closed this gap! Welcome to my third post about Azure Data Factory V2. Azure Data Factory 2. You can operationalize Databricks notebooks in Azure Data Factory data pipelines. Azure Data Factory is a hybrid data integration service that allows you to create, schedule and orchestrate your ETL/ELT workflows at scale wherever your data lives, in cloud or self-hosted network. Azure SQL Data Warehouse offers elastic scale and massive parallel processing. The ACL (access control list) grants permissions to to create, read, and/or modify files and folders stored in the ADLS service. Our goal is to simplify the Azure Data Factory authoring experience and remove on-boarding and deployment challenges. Azure Data Factory Data Flow or ADF-DF (as it shall now be known) is a cloud native graphical data transformation tool that sits within our Azure Data Factory platform as a service product. As of March 2018, Neptune is in Preview, so the documentation is likely to change in the coming weeks (well, that's my assumption, because Neptune has been in Preview since November. Configure an Azure Application Connection. SSIS has been. Hey there! In the second part of my Azure Data Factory best practices I'll be talking about controlling the flow of your tasks. you want to load data to different locations in Blob. PowerShell. The official account for Microsoft Azure. In this post I outline an approach to leverage and extract data out of Excel files as part of an Azure Data Factory pipeline. Azure Data Factory V2 is the go-to service for moving large amounts of data within the Azure platfor Using Lookup, Execute Pipeline and For Each Activity in Azure Data Factory V2 In my previous blog I looked how we can utilise pipeline parameters to variablise certain aspects of. Use the Azure Cosmos DB Spark connector. Configure an Azure Application Connection. I've used Azure SQL (via Data Factory) to generate 10,000 JSON objects, that are stored on a table. The Data Science VM can readily leverage these services in Azure to support the deployment of large scale enterprise team -based Data Science and AI environments. IoT is a game-changer Harness the power of IoT and the cloud in your manufacturing environment to monitor performance, optimize operations and solve problems remotely, all using the Microsoft Azure IoT connected factory preconfigured solution that can be customized to your needs. We have a Azure Data Factory, hosted in EastUS data center. That will open a separate tab for the Azure Data Factory UI. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Authenticating Sign in. The pipeline definition includes a query. From the Template Gallery, select Copy data from on-premise SQL Server to SQL Azure. Best Practices for Using Azure Data Lake Store. Pause and Resume Azure Data Warehouse Solution You could solve this with a scripting language like PowerShell and run that PowerShell script each morning and evening with SQL Server Agent or Windows Scheduler, but for this solution I will use Azure Runbook with its scheduler. you will also learn features that are available in ADF but not. The sheer volume of data can be enormous, and it often arrives from multiple locations and is needed for time-critical operations. Contribute to kromerm/adfdataflowdocs development by creating an account on GitHub. Deploy and manage multiple websites with the help of Acquia Cloud Site Factory. Apps Consulting Non-disruptive SAN storage migration from any legacy data center to Azure Cloud. By Prasad Kona Organizations have been increasingly moving towards and adopting cloud data and cloud analytics platforms like Microsoft Azure. In this post we want to take the first step in building components of Azure Data Factory. Azure Marketplace. However, Azure Data Factory V2 has finally closed this gap! Welcome to my third post about Azure Data Factory V2. See user reviews of Talend Data Management Platform. Data Factory. Azure supports various data stores such as source or sinks data stores like Azure Blob storage, Azure Cosmos DB (DocumentDB API), Azure Data Lake Store, Oracle, Cassandra, etc. How to extract data and load using Azure Data Factory 2350 Mission College Boulevard, Suite 925, Santa Clara, California, 95054 USA: Atlanta l Chicago l New Jersey l Philadelphia India: Bangalore l Hyderabad. Top-level concepts. In this follow-up I answer all the important questions that were posted to the Q&A pannel, like those related to the return of fun facts. We will continue to. Get an overview of advanced analytics, and see how Azure Data Factory fits into the Cortana Analytics Suite. Now ADF is coming up with a Data Flow activity which allows developing GUI bases transformations. Azure Data Factory. Linked Services are connection to data sources and destinations. Azure Certified for IoT device catalog has a growing list of devices from hundreds of IoT hardware manufacturers to help you build your IoT solution. It is a serverless orchestrator where you can create pipelines that represent a workflow. Azure Data Lake Storage Gen1 enables you to capture data of any size, type, and ingestion speed in a single place for operational and exploratory analytics. Microsoft is radically simplifying cloud dev and ops in first-of-its-kind Azure Preview portal at portal. Azure Data Factory is a managed service on cloud which provides ability to extract data from different sources, transform it with data driven pipelines, and process the data. Azure Data Lake - The Services. Access Control in Azure Data Lake Store. At Microsoft, with the announcement of v2 of the Azure Data Factory service (ADF) preview service, we've invested in expanding the data integration service in Azure to enable a series of new use cases that we found to be very popular and very common in cloud-first ETL and data integration scenarios. Data Flow is a new feature of Azure Data Factory (ADF) that allows you to develop graphical data transformation logic that can be executed as activities within ADF pipelines. This process will automatically export records to Azure Data Lake into CSV files over a recurring period, providing a historical archive which will be available to various routines such as Azure Machine Learning, U-SQL Data Lake Analytics or other big data style. 0 takes data integration to the next level and comes with a variety of triggers, integration with SSIS on-prem & in Azure, integration with Azure Monitor, control flow branching and. Azure Data Factory Documentation Learn how to use Data Factory, a cloud data integration service, to compose data storage, movement, and processing services into automated data pipelines. It has connectors for more than 70 different data services, features an easy-to-use drag-and-drop interface, supports multiple programming languages and is highly scalable. Connect the Splunk Add-on for Microsoft Cloud Services and your Azure Storage account so that you can ingest your Azure storage table, Azure storage blob and Azura virtual machine metrics data into the Splunk platform. Conclusion. Usually the very first step is creating Linked Services. Mark Harrison. Getting Started With Apache Hive Software¶. Azure Data Factory V2 is the data integration platform that goes beyond Azure Data Factory V1's orchestration and batch-processing of time-series data, with a general purpose app model supporting modern data warehousing patterns and scenarios, lift-and-shift SSIS, and data-driven SaaS applications. what is needed to connect to and monitor Azure Data Factory. Infuse your apps, websites and bots with intelligent algorithms to see, hear, speak, understand and interpret your user needs thro. By Prasad Kona Organizations have been increasingly moving towards and adopting cloud data and cloud analytics platforms like Microsoft Azure. Enter Azure Data Factory 2. From there, you can use CrateDB (hosted on Microsoft Azure) to query and analyze the data in real-time. Data Flow is a new feature in Azure Data Factory currently available in limited preview that enables cloud based, code free, data transformations at scale, directly within Azure Data Factory's visual authoring experience. 0 takes data integration to the next level and comes with a variety of triggers, integration with SSIS on-prem & in Azure, integration with Azure Monitor, control flow branching and. For data that’s in Azure blob storage, you can use a CLI tool called AdlCopy. About 3 weeks ago I presented a free webinar for Pragmatic Works where I talked about Azure Data Factory V2. Not having this closes the door to lots of integration scenarios. What is Azure Data Factory? Consultants: Corp-to-Corp vs 1099 Factless fact table Why You Need a Data Warehouse Relational databases vs Non-relational databases Operational Data Store (ODS) Defined Azure Data Explorer Parallel execution in SSIS Azure Data Factory Data Flow Azure Data Factory and SSIS compared. From SQL Server tips to videos, we can help you. We want to move that to WestUS data center, as our VMs reside in the WestUS datacenter. I have tried the following JSON in the output data set but it stills writes it as a string. Monitoring the pipeline of data, validation and execution of scheduled jobs Load it into desired Destinations. NET, Powershell). Azure Data Factory - Iterate over a data collection using Lookup and ForEach Activities - Duration: 36:07. Azure Data Factory is Microsoft Cloud based ETL technology, which has ability to work with large volume of data, working with data sources such as SQL Server on premises, SQL Server Azure, or Azure Blob storage. Azure Data Factory is a managed service on cloud which provides ability to extract data from different sources, transform it with data driven pipelines, and process the data. Introduction. The pulling part works fine but have couple of issues that need help with. If you have. Hey there! In the second part of my Azure Data Factory best practices I'll be talking about controlling the flow of your tasks. This was a simple copy from one folder to another one. Getting Started With Apache Hive Software¶. In my previous post, we've went through the new features of Azure Data Factory 2. 0 takes data integration to the next level and comes with a variety of triggers, integration with SSIS on-prem and in Azure, integration with Azure Monitor, control flow branching. Get an overview of advanced analytics, and see how Azure Data Factory fits into the Cortana Analytics Suite. Cognitive Services. Azure Data Factory V2 is the go-to service for moving large amounts of data within the Azure platfor Using Lookup, Execute Pipeline and For Each Activity in Azure Data Factory V2 In my previous blog I looked how we can utilise pipeline parameters to variablise certain aspects of. The hadoop-azure module includes a full suite of unit tests. Therefore, Linked Services enables you to define data sources, or compute resource that are required to ingest and prepare data. In a similar way that SQL Server Integration Services (SSIS) can be used to transform and load data in on. On the other hand, if you are already using Azure Data Factory, you most likely have a title like Data Engineer, ETL Developer, Data Integrator, Business Intelligence Consultant, or something similar. Analysis Services. The Azure Cosmos DB Spark Connector User Guide, developed by Microsoft, also shows how to use this connector. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. You can find it here: Azure Data Factory V2 Preview Documentation. Azure Data Factory Data Flow Documentation. In this post we want to take the first step in building components of Azure Data Factory. Our goal is to simplify the Azure Data Factory authoring experience and remove on-boarding and deployment challenges. Now ADF is coming up with a Data Flow activity which allows developing GUI bases transformations. Most other Microsoft services (Office 365, PWA, CRM, etc, etc, etc) along with many other industry API's require the use of OAuth. Azure Data Factory V2 is the go-to service for moving large amounts of data within the Azure platfor Using Lookup, Execute Pipeline and For Each Activity in Azure Data Factory V2 In my previous blog I looked how we can utilise pipeline parameters to variablise certain aspects of. Yesterday at TechEd Europe 2014, Microsoft announced the preview of Azure Data Factory. We want to move that to WestUS data center, as our VMs reside in the WestUS datacenter. You will also need a compute resource for your custom activity. Power BI Embedded Embed fully interactive, stunning data visualizations in your applications. Provided "as is" with no warranties, and confer no rights. You define the parameters of your data transformations and AWS Data Pipeline enforces the logic that. Congrats on the launch of the service! Awesome to see Azure App Service - literally another -aaS no less! Definitely going to check out the automation (especially the agility & scalability) and the orchestration (the workflow engine & UX) as well as the API ecosystem, which looks like it will play well with my big data analytics hobby projects :). For help, please contact @AzureSupport. For more information about Data Factory supported data stores for data movement activities, refer to Azure documentation for Data movement activities. While there were. As the name implies, this is already the second version of this kind of service and a lot has changed since its predecessor. The hadoop-azure module includes a full suite of unit tests. I have usually described ADF as an orchestration tool instead of an Extract-Transform-Load (ETL) tool since it has the “E” and “L” in ETL but not the “T”. Uploading Files to Azure Data Lake Using a. Need to schedule and manage big data workflows? This data analysis course teaches you how to use Azure Data Factory to coordinate data movement and transformation using technologies such as Hadoop, SQL, and Azure Data Lake Analytics. Course – Basics of KQL. From the Template Gallery, select Copy data from on-premise SQL Server to SQL Azure. Apr 29, 2015 · Microsoft today announced Azure Data Lake, a new data repository for big data analytics workloads, during its Build developer conference keynote. Monitoring the pipeline of data, validation and execution of scheduled jobs Load it into desired Destinations. In a similar way that SQL Server Integration Services (SSIS) can be used to transform and load data in on. The sheer volume of data can be enormous, and it often arrives from multiple locations and is needed for time-critical operations. Microsoft readies new Azure Data Factory service. Get an overview of advanced analytics, and see how Azure Data Factory fits into the Cortana Analytics Suite. Usually the very first step is creating Linked Services. Azure Automation. Is it possible to use Azure Data Factory to get data from a REST API and insert it to a Azure database table?. Azure supports various data stores such as source or sinks data stores like Azure Blob storage, Azure Cosmos DB (DocumentDB API), Azure Data Lake Store, Oracle, Cassandra, etc. Net, or Visual Studio. We would like to build test environment for Azure Data Factory pipeline jobs before moving to production. Step 1: Create Storage account and a container in Azure. In this post I …Continue reading Using Azure Resource Manager Templates with Azure Data Factory. Data Factory Hybrid data integration at enterprise scale, made easy; Machine Learning Build, train, and deploy models from the cloud to the edge; Azure Stream Analytics Real-time data stream processing from millions of IoT devices; Azure Data Lake Storage Massively scalable, secure data lake functionality built on Azure Blob Storage. 3 The NuGet Team does not provide support for this client. Access Control in Azure Data Lake Store. Azure Data Factory. Datasets represent data structures within the data store that is being referenced by the Linked Service object. In my previous post, we've went through the new features of Azure Data Factory 2. Exploring data orchestration concepts? Check out this course on the basic capabilities of Azure Data Factory (ADF). If the data is already in an HDFS (Hadoop Distributed File System) store, you can use tools like Sqoop or DistCp. Find the solution that's right for you. The sheer volume of data can be enormous, and it often arrives from multiple locations and is needed for time-critical operations. If you want to move data on a schedule, another option is Azure Data Factory. Azure Data Factory is a fully managed data processing solution offered in Azure. Microsoft readies new Azure Data Factory service. Original Data Data Load Transformed Transform BI Tools Ingest (EL) Apps Original Data Scale-out Storage & Compute (HDFS, Blob Storage, etc) Transform & Load Data Marts Data Lake(s) Dashboards Streaming data. Cannot find an answer via google, msdn (and other microsoft) documentation, or SO. The Data Science VM can readily leverage these services in Azure to support the deployment of large scale enterprise team -based Data Science and AI environments. About Azure Data Factory (ADF) The ADF service is a fully managed service for composing data storage, processing, and movement services into streamlined, scalable, and reliable data production pipelines. 15 Data Factory v2 in Azure Portal 13. However, Azure Data Factory V2 has finally closed this gap! Welcome to my third post about Azure Data Factory V2. Today's business managers depend heavily on reliable data integration systems that run complex ETL/ELT workflows (extract, transform/load and load/transform data). A simplistic view is that Azure data factory (ADF) is the cloud evolution of SQL Server Integration Services (SSIS) - the tool traditionally used to perform Extract, Transform and Load (ETL) operations from hetergenous data sources into an Enterprise data warehouse that ships with the on-premises MS SQL server product. As a supplement to the documentation provided on this site, see also docs. Partitioning and wildcards in an Azure Data Factory pipeline In a previous post I created an Azure Data Factory pipeline to copy files from an on-premise system to blob storage. 0 that is now in public preview. I've used Azure SQL (via Data Factory) to generate 10,000 JSON objects, that are stored on a table. The Azure Data Factory task enables the execution of Azure Pipelines as part of a Data Governor job. Net, or Visual Studio. The following Scala notebook provides a simple example of how to write data to Cosmos DB and read data from Cosmos DB. During Ignite, Microsoft announced Azure Data Factory 2. On the left side you will find links to the different articles and on the main page links to the excellent step-by-step tutorials. Azure Data Lake is based on the Apache Hadoop YARN (Yet Another Resource Negotiator) cluster management platform and is intended to scale dynamically across SQL servers in Azure Data Lake, as well as servers in Azure. Contact Support.