What is Azure Data Lake?
We’ve been hearing a lot about the Microsoft Azure cloud platform. With all of the talk about cloud and the different Azure components available, it can get confusing. So what is Azure Data Lake? Microsoft Azure Data Lake is part of the Microsoft Azure public cloud platform, which includes more than 200 products and cloud services. Azure Data Lake is a cloud platform designed to support big data analytics. It provides unlimited storage for structured, semi-structured or unstructured data. It can be used to store any type of data of any size.
How does Azure Data Lake Work?
Azure Data Lake is built on Azure Blob storage, which is the Microsoft object storage solution for the cloud. The solution matifeatures low-cost, tiered storage and high-availability/disaster recovery capabilities. It integrates with other Azure services, including Azure Data Factory, which is a tool for creating and running extract, transform and load (ETL) and extract, load and transform (ELT) processes.
The solution is based on the Apache Hadoop YARN (Yet Another Resource Negotiator) cluster management platform. It can scale dynamically across SQL servers within the data lake, as well as servers in Azure SQL Database and Azure SQL Data Warehouse.
To begin using Azure Data Lake, create a free account on the Microsoft Azure portal. From the portal, you can access all of the Azure services.
What are the Three Parts of Azure Data Lake?
The full solution consists of three components that provide storage, an analytics service and cluster capabilities.
Azure Data Lake Storage is a massively scalable and secure data lake for high-performance analytics workloads. Azure Lake Data Storage was formerly known and is sometimes still referred to as the Azure Data Lake Store. Designed to eliminate data silos, Azure Data Lake Storage provides a single storage platform that organizations can use to integrate their data. Azure Data Lake Storage can help optimize costs with tiered storage and policy management. It also provides role-based access controls and single sign-on capabilities through Azure Active Directory. Users can manage and access data within Azure Data Lake Storage using the Hadoop Distributed File System (HDFS). Therefore any tool that you’re already using that is based on HDFS will work with Azure Data Lake Storage.
Azure Data Lake Analytics is an on-demand analytics platform for big data. Users can develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and .NET over petabytes of data. (U-SQL is a big data query language created by Microsoft for the Azure Data Lake Analytics service.) With Azure Data Lake Analytics, users pay per job to process data on demand in an analytics as a service environment. Azure Data Lake Analytics is a cost-effective analytics solution because you pay only for the processing power that you use.
Azure HDInsight is a cluster management solution that makes it easy, fast, and cost-effective to process massive amounts of data. It’s a cloud deployment of Apache Hadoop that enables users to take advantage of optimized open source analytic clusters for Apache Spark, Hive, Map Reduce, HBase, Storm, Kafka, and R-Server. With these frameworks, you can support a broad range of functions, such as ETL, data warehousing, machine learning, and IoT. Azure HDInsight also integrates with Azure Active Directory for role-based access controls and single sign-on capabilities.
Who Needs Azure Data Lake & Why?
The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format, and perform all types of processing and analytics across multiple platforms and programming languages. It can work with your existing solutions, such as identity management and security solutions. It also integrates with other data warehouses and cloud environments. It can be useful for organizations that need the following:
Because the solution supports any type of data, you can use it to integrate all of your enterprise data in a single data warehouse.
Internet of Things (IoT) capabilities
The Azure platform provides tools for processing streaming data in real time from multiple types of devices.
Support for hybrid cloud environments
You can use the Azure HDInsight component to extend an existing on-premises big data infrastructure to the Azure cloud.
The environment is managed and supported by Microsoft and includes enterprise features for security, encryption and governance. You can also extend your on-premises security solutions and controls to the Azure cloud environment.
Speed to deployment
It’s pretty easy to get up and running quickly with the Azure Data Lake solution. All of the components are available through the portal and there are no servers to install and no infrastructure to manage.
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