{"id":775,"date":"2024-02-28T09:00:00","date_gmt":"2024-02-28T17:00:00","guid":{"rendered":""},"modified":"2024-02-28T13:03:07","modified_gmt":"2024-02-28T21:03:07","slug":"microsoft-is-recognized-as-a-leader-in-the-forrester-wave-streaming-data-platforms","status":"publish","type":"post","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/2024\/02\/28\/microsoft-is-recognized-as-a-leader-in-the-forrester-wave-streaming-data-platforms\/","title":{"rendered":"Microsoft is recognized as a Leader in The Forrester Wave\u2122: Streaming Data Platforms"},"content":{"rendered":"<aside id=\"accordion-6d8b47d2-142a-454d-b21c-6e578d2a2a19\" class=\"table-of-contents-block accordion pb-0\" data-bi-aN=\"table-of-contents\">\n\t<button class=\"btn btn-collapse mb-0 display-flex justify-content-between w-100\" type=\"button\" data-mount=\"collapse\" data-target=\"#accordion-collapse-6d8b47d2-142a-454d-b21c-6e578d2a2a19\" aria-expanded=\"true\" aria-controls=\"accordion-collapse-6d8b47d2-142a-454d-b21c-6e578d2a2a19\">\n\t\t<span class=\"table-of-contents-block__label subtitle\">In this article<\/span>\n\t\t<span class=\"table-of-contents-block__current mr-4 text-gray-600 font-weight-normal\" aria-hidden=\"true\"><\/span>\n\n\t\t<svg class=\"table-of-contents-block__arrow\" aria-label=\"Toggle arrow\" width=\"18\" height=\"11\" viewBox=\"0 0 18 11\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n\t\t\t<path d=\"M15.7761 11L18 8.82043L9 0L0 8.82043L2.22394 11L9 4.35913L15.7761 11Z\" fill=\"currentColor\" \/>\n\t\t<\/svg>\n\t<\/button>\n\t<div id=\"accordion-collapse-6d8b47d2-142a-454d-b21c-6e578d2a2a19\" class=\"table-of-contents-block__collapse-wrapper collapse show\" data-parent=\"#accordion-6d8b47d2-142a-454d-b21c-6e578d2a2a19\">\n\t\t<div class=\"accordion-body p-0\">\n\t\t\t<ol class=\"table-of-contents-block__list\"><li class=\"table-of-contents-block__list-item\"><a class=\"table-of-contents-block__list-item-link\" href=\"#why-is-stream-processing-important\">Why is Stream processing important?\u202f\u202f\u00a0<\/a><\/li><li class=\"table-of-contents-block__list-item\"><a class=\"table-of-contents-block__list-item-link\" href=\"#why-do-customers-love-azure-streaming-data-platform\">Why do customers love Azure Streaming Data Platform?\u202f\u00a0<\/a><\/li><li class=\"table-of-contents-block__list-item\"><a class=\"table-of-contents-block__list-item-link\" href=\"#the-road-ahead-with-fabric-real-time-analytics\">The road ahead with Fabric Real-Time Analytics\u202f\u00a0<\/a><\/li><li class=\"table-of-contents-block__list-item\"><a class=\"table-of-contents-block__list-item-link\" href=\"#discover-solutions\">Discover solutions<\/a><\/li><\/ol>\t\t<\/div>\n\t<\/div>\n\t<span class=\"table-of-contents-block__progress-bar\"><\/span>\n<\/aside>\n\n\n\n<p>In today&#8217;s rapidly evolving data and AI landscape, the demand for comprehensive event and streaming analytics solutions has never been more critical. Over the past few years, Microsoft has dedicated itself to investing in this area and addressing the needs of its customers by offering seamless and powerful options for stream processing. This includes <a href=\"https:\/\/learn.microsoft.com\/en-us\/fabric\/real-time-analytics\/overview\">Microsoft Fabric Real-Time Analytics<\/a>, a robust solution built upon the scalable, fault-tolerant foundations of Azure Streaming Data Platform services.\u202f<\/p>\n\n\n\n<p>We\u2019re excited to announce that our investments are paying off. Microsoft has been recognized as a <strong>Leader<\/strong> in The Forrester Wave\u2122: Streaming Data Platforms, Q4 2023\u2014a distinction based on Forrester\u2019s evaluation of the advanced capabilities of Azure Event Hubs and Azure Stream Analytics services.\u202f\u202f&nbsp;<\/p>\n\n\n\n<p><strong>Microsoft not only secured the highest score among all vendors in the \u201ccurrent offering\u201d category, but was also given the top score possible of 5.0 across 13 distinct criteria<\/strong>.<strong> <\/strong>The Forrester report acknowledges Microsoft\u2019s strengths\u202fin streaming analytics, low latency, fault tolerance, and developer tools. You can read the full <a href=\"https:\/\/reprints2.forrester.com\/#\/assets\/2\/108\/RES178464\/report\" target=\"_blank\" rel=\"noreferrer noopener\">The Forrester Wave\u2122: Streaming Data Platforms, Q4 2023<\/a> to learn more about Microsoft\u2019s position as a leader in the evaluation.\u202f\u202f&nbsp;<\/p>\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img decoding=\"async\" src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave-739x1024.webp\" alt=\"The Forrester Wave&trade; Streaming Data Platform figure\" class=\"wp-image-782 webp-format\" style=\"width:627px;height:auto\" srcset=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave-739x1024.webp 739w, https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave-216x300.webp 216w, https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave-768x1064.webp 768w, https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave.webp 889w\" data-orig-src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Forrester-Wave-739x1024.webp\"><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"why-is-stream-processing-important\">Why is Stream processing important?\u202f\u202f&nbsp;<\/h2>\n\n\n\n<p><strong>Stream processing<\/strong> has emerged as a crucial technology, revolutionizing the way data is collected, analyzed, and <strong>insight-based decisions<\/strong> are made, all in <strong>real-time<\/strong>. But the benefits of stream processing extend beyond just speed. It gives organizations a holistic 360-degree view of real-time and batch data empowering them to detect anomalies, identify patterns, and extract valuable insights from the continuous influx of data. This not only enhances decision-making processes but also enables businesses to deliver personalized and responsive experiences to their customers. With reduced latency and immediate feedback loops, stream processing fosters a <strong>more agile<\/strong> and <strong>adaptive<\/strong> approach to data-driven decision-making, ultimately contributing to increased <strong>efficiency<\/strong>, <strong>innovation<\/strong>, and a critical edge in today&#8217;s competitive market.\u202f&nbsp;<\/p>\n\n\n\n<p>However, stream processing at a cloud scale can be challenging for businesses, both large and small. Integration complexities with existing services, the need for efficient resource scaling, ensuring reliability and fault tolerance, and addressing security concerns pose significant hurdles. Striking a balance between seamless integration, scalable infrastructure, and robust security measures is crucial for successful cloud-based stream processing implementations.\u202f\u202f&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"why-do-customers-love-azure-streaming-data-platform\">Why do customers love Azure Streaming Data Platform?\u202f&nbsp;<\/h2>\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Azure-Streaming-Data-Platform.webp\" alt=\"Azure Streaming Data Platform architecture\" class=\"wp-image-783 webp-format\" srcset=\"\" data-orig-src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Azure-Streaming-Data-Platform.webp\"><\/figure>\n\n\n\n<p>Microsoft Azure addresses these challenges with one powerful solution on two products\u2014Azure Event Hubs and Azure Stream Analytics. <a href=\"https:\/\/azure.microsoft.com\/en-in\/products\/event-hubs\/\" target=\"_blank\" rel=\"noreferrer noopener\">Azure Event Hubs<\/a> provides a <strong>scalable<\/strong> and <strong>open<\/strong> event ingestion service, simplifying the integration of stream processing frameworks. Complementing this, <a href=\"https:\/\/azure.microsoft.com\/en-us\/products\/stream-analytics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Azure Stream Analytics<\/a> enables users to build and deploy complex stream processing queries. Together, these services enable businesses to ingest, process, and analyze <strong>massive amounts of data<\/strong> in real-time. With built-in <strong>security<\/strong>, <strong>reliability<\/strong> features, and developer tools, Microsoft Azure services ensure data protection, <strong>business continuity<\/strong>, and <strong>productivity<\/strong>\u2014at a <strong>flexible price point<\/strong> that makes stream processing at scale affordable for all Azure customers.\u202f\u202f\u202f&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Ingestion and stream analytics<\/strong>: Azure Event Hubs has native, on-by-default support for Open standards such as Apache Kafka and AMQP, enabling customers to ingest data from a wide variety of data sources. Meanwhile, Azure Stream Analytics supports output data into multiple services including Microsoft Power BI, Azure Functions, Azure SQL, and Azure Data Lake Storage. The support for Delta Lake (Delta Parquet) enables customers to persist the output of the stream analytics process in a way that can then be consumed by popular analytics services like Fabric, Azure Synapse, and Azure Databricks. By facilitating seamless integration between best-in-class tools and frameworks, Azure Streaming Data Platform services ensure that data flows smoothly from ingestion through to analytics, optimizing the value Azure customers can derive from their data assets.\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>High scale (latency and throughput)<\/strong>: Azure Streaming Data Platform services are the backbone for thousands of leading enterprises that have come to depend upon the proven performance at planet scale. Azure Event Hubs has consistently exceeded the OpenMessaging Benchmark standards demonstrating end-to-end latency of under 10 milliseconds. Additionally, Azure Streaming Analytics, built upon multiple patented optimizations, supports data processing at a throughput of several GBs per second. These two services are handling over 10 trillion requests and more than 13 PB data ingested per day. This combination of low latency and high throughput equips businesses with the capability to manage, process, and analyze vast volumes of data at a very high velocity. This enables businesses to gain a significant advantage by making quicker, more informed decisions, and staying ahead of their competitors in today\u2019s fast-paced market.\u202f\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Fault tolerance and reliability<\/strong>: Built upon the robust, fault-tolerant foundation of Microsoft Azure and features such as availability zones, the Azure Streaming Data Platform is engineered for resilience. This ensures an unparalleled level of reliability and fault tolerance, providing our customers with peace of mind through a financially backed 99.99% uptime guarantee. Thousands of customers across various industries rely on our Streaming Data Platform services for their mission-critical applications, trusting in our platform&#8217;s consistent performance, reliability and the assurance of operational continuity, even in the face of unexpected challenges.\u202f\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Security and privacy<\/strong>: Security is paramount in the digital age, and Azure takes this seriously. Both Azure Event Hubs and Azure Stream Analytics come fortified with robust security capabilities. Features such Microsoft Entra-based modern authentication, full compute isolation with dedicated clusters, native VNET integration, and end-to-end encryption using customer managed keys (CMK) ensures that businesses can navigate the data landscape with confidence, knowing that their valuable information is not just processed but safeguarded with the highest standards of security and privacy.\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Developer productivity<\/strong> <strong>and tools<\/strong>: Azure&#8217;s commitment to high productivity is reflected in the suite of developer tools like Visual Studio Code, user-friendly web interfaces, and the low-code\/no-code experiences of both Azure Event Hubs and Stream Analytics. Features such as \u201ccapture data\u201d and \u201cprocess data\u201d are designed to simplify routine tasks, enabling data engineers to quickly accomplish their objectives without the need to navigate through complex configurations, service integrations, or job scheduling and monitoring. This focus on streamlining the development experience not only boosts efficiency but also accelerates the deployment of data-driven solutions, enabling teams to focus on innovation rather than administrative overheads.\u202f\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Streaming in the age of AI<\/strong>: The integration of machine learning features amplifies the analytical capabilities of Azure&#8217;s streaming solutions in this age of AI including anomaly and fraud detection. The ability to call out to real-time scoring APIs and Azure Cognitive APIs from Azure Stream Analytics jobs are just the start.\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Pricing flexibility<\/strong>: Achieving business efficiency, customer satisfaction, and user productivity shouldn&#8217;t come at an exorbitant cost. To that end, Azure Event Hubs and Azure Stream Analytics offer a variety of flexible pricing options tailored to meet the needs of businesses and use cases of all sizes. Whether you&#8217;re a small startup or a large enterprise, our pricing models are designed to provide cost-effective access to advanced stream processing capabilities. This approach ensures that businesses can leverage the power of real-time data analytics without compromising on financial objectives, ultimately driving better business outcomes, enhancing customer satisfaction, and promoting overall productivity.\u202f\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Globally available<\/strong>: Azure Event Hubs and Azure Stream Analytics services are available in over 60 Azure regions around the globe. This number keeps growing to meet more customer demand. So, whether Azure customers need high-speed network access or have data sovereignty requirements, Stream Processing services are always in a region near them.\u202f&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>If you are looking for a cloud-based streaming data platform that offers reliability, openness, performance, and affordability, look no further than Microsoft Azure. Azure Event Hubs and Azure Stream Analytics are the leading solutions in the market, enabling you to harness the power of stream processing for your business needs with ease and promoting a culture of innovation without unnecessary complexity.\u202fAnd we are not done! With Microsoft Fabric Real-Time Analytics and Data Activator, we have taken the next steps towards an even more accessible and seamless Software as a Service (SaaS) experience for you.\u202f&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"the-road-ahead-with-fabric-real-time-analytics\">The road ahead with Fabric Real-Time Analytics\u202f&nbsp;<\/h2>\n\n\n\n<p>Microsoft Fabric Real-Time Analytics offers a powerful suite of features for handling real-time data, all seamlessly integrated under a consistent user experience, security model, and capacity model. <strong>Event streams<\/strong> enables ingestion and processing of streaming data from a wide variety of sources including Kafka, Azure, and into Fabric Lakehouse and <strong>Kusto Query Language (KQL) databases<\/strong>, enabling efficient analytics, real-time dashboarding, anomaly detection, and monitoring. <strong>Data Activator<\/strong> empowers users to define actionable patterns within their data, from simple thresholds to complex trends, driving informed decisions and alerts. All together, Fabric Real-Time Analytics and Data Activator provide a low-code\/no-code experience for high-volume, high-granularity data within the unified AI-power analytics platform of Microsoft Fabric.\u202f\u202f&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"discover-solutions\">Discover solutions<\/h2>\n\n\n\n<p>Learn more streaming data platforms on Azure and Microsoft Fabric:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/azure.microsoft.com\/en-us\/products\/event-hubs\/\" target=\"_blank\" rel=\"noreferrer noopener\">Microsoft Azure Event Hubs<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/azure.microsoft.com\/en-us\/products\/stream-analytics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Microsoft Azure Stream Analytics<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/learn.microsoft.com\/en-us\/fabric\/real-time-analytics\/overview\">Real-Time Analytics in Fabric<\/a><\/li>\n<\/ul>\n\n\n<div class=\"wp-block-msxcm-cta-block\" data-moray data-bi-an=\"CTA Block\">\n\t<div class=\"card d-block mx-ng mx-md-0\">\n\t\t<div class=\"row no-gutters material-color-brand-dark bg-fabric-green\">\n\n\t\t\t\t\t\t\t<div class=\"col-md-4\">\n\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"600\" height=\"600\" src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Comp2-4K.png\" class=\"card-img img-object-cover\" alt=\"Abstract image\" srcset=\"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Comp2-4K.webp 600w, https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Comp2-4K-300x300.webp 300w, https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-fabric\/blog\/wp-content\/uploads\/2024\/02\/Comp2-4K-150x150.webp 150w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/>\t\t\t\t<\/div>\n\t\t\t\n\t\t\t<div class=\"d-flex col-md\">\n\t\t\t\t<div class=\"card-body align-self-center p-4 p-md-5\">\n\t\t\t\t\t\n\t\t\t\t\t<h2>Real-Time Analytics in Fabric<\/h2>\n\n\t\t\t\t\t<div class=\"mb-3\">\n\t\t\t\t\t\t<p>Reduce complexity and simplify data integration<\/p>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"link-group\">\n\t\t\t\t\t\t\t<a href=\"https:\/\/learn.microsoft.com\/en-us\/fabric\/real-time-analytics\/overview\" class=\"btn btn-link text-decoration-none p-0\" target=\"_blank\">\n\t\t\t\t\t\t\t\t<span>Read the documentation<\/span>\n\t\t\t\t\t\t\t\t<span class=\"glyph-append glyph-append-chevron-right glyph-append-xsmall\"><\/span>\n\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\t\t\t\t\t<\/div>\n\t<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Microsoft has been recognized as a Leader in The Forrester Wave\u2122: Streaming Data Platforms, Q4 2023\u2014a distinction based on Forrester\u2019s evaluation of the advanced capabilities of Azure Event Hubs and Azure Stream Analytics services.<\/p>\n","protected":false},"author":26,"featured_media":823,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ms_queue_id":[],"ep_exclude_from_search":false,"_classifai_error":"","_classifai_text_to_speech_error":"","footnotes":""},"post_tag":[54,75,62,46,71],"content-type":[63],"coauthors":[91],"class_list":["post-775","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","tag-azure","tag-azure-data-lake-storage","tag-microsoft-power-bi","tag-onelake","tag-real-time-analytics","content-type-industry-trends"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Microsoft is recognized as a Leader in Streaming Data Platforms | Microsoft Fabric Blog<\/title>\n<meta name=\"description\" content=\"Microsoft is dedicated to investing and addressing the needs of its customers by offering seamless and powerful options for stream processing. 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