{"id":315,"date":"2022-03-02T23:07:18","date_gmt":"2022-03-02T23:07:18","guid":{"rendered":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/?p=315"},"modified":"2025-11-17T05:14:02","modified_gmt":"2025-11-17T05:14:02","slug":"etl-modernization-reduce-migration-timelines-and-unlock-scalabilty-and-real-time-data-processing","status":"publish","type":"post","link":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/blog\/etl-modernization-reduce-migration-timelines-and-unlock-scalabilty-and-real-time-data-processing\/","title":{"rendered":"ETL Modernization: Reduce Migration Timelines and Achieve Scalable, Real-Time Data Processing"},"content":{"rendered":"<p class=\"intro-box\">The cloud evolution is no longer a movement for modern business, it\u2019s an inescapable reality. A vastly greater amount of data sources, the volume of customer data, and disruptions to the supply chain call for companies to fully utilize the cloud and its unlimited compute and capacity. To keep up, organizations need real-time data processing for scalability and to empower decision-makers with data faster. But for many, a barrier for <a href=\"https:\/\/wavicledata.com\/guides\/cloud-migration-taking-your-data-and-analytics-to-the-cloud\/\">cloud migration<\/a>, cloud utilization and data integration remains \u2014 in the form of traditional extract, transform, and load (ETL) platforms. At Wavicle, we create ETL migration and modernization strategies at a holistic level based on business processes and goals, use cases, and current technology stacks. For AWS users, AWS Glue is a serverless and scalable data integration option.<\/p>\r\n\r\n<h2>Traditional ETL weaknesses<\/h2>\r\n<p class=\"intro-box\">\u00a0 Traditional ETL processes consist of the development of batched data pipelines for on-premise sources tied to conventional hardware infrastructure. While still necessary today, the technology isn\u2019t for high-speed processing. Legacy ETL platforms are mostly designed for relational databases and other traditional data sources. For today\u2019s exponentially increased pace, volume, and multi-source data, legacy ETL platforms do not have the agility to transform data at the speed for loading into a data warehouse or data lake. Beyond the inability to keep up with the momentum of modern big data, legacy ETL platforms come with other inherent shortcomings.<\/p>\r\n\r\n<h4>Time<\/h4>\r\n<p class=\"intro-box\">Legacy ETL platforms are slow from a user perspective. When a company has thousands or tens of thousands of ETL jobs for moving data or applications to the cloud, timelines become a serious pain point.<\/p>\r\n\r\n<h4>Cost<\/h4>\r\n<p class=\"intro-box\">For platforms like Informatica, Datastage, or other legacy ETL solutions, licensing costs present a major financial burden for growing organizations. These tools contain their engines for data transformation, requiring investment into servers and storage. With modern ETL platforms like AWS Glue, the vendor absorbs the infrastructure cost.<\/p>\r\n\r\n<h4>Lack of open-source<\/h4>\r\n<p class=\"intro-box\">Legacy ETL platforms are not designed as open-source and subsequently, have serious limitations for integrating with other open-source technology like Databricks. According to an IBM survey, open-source software was rated equal to or better than proprietary software by 94% of respondents.<\/p>\r\n\r\n<h4>Scalability<\/h4>\r\n<p class=\"intro-box\">Legacy ETL platforms were not designed for the cloud. This means they aren\u2019t capable of unlimited scalability, an inherent value pillar for the cloud. The lack of cloud design also means many tools won\u2019t support cloud-base.<\/p>\r\n\r\n<h4>Maintenance<\/h4>\r\nMaintenance, upgrades, and renewals of legacy ETL platforms require dedicated managers. These time-consuming processes and operations drain internal team resources and bandwidth. With AWS Glue and other modern ETL tools, most services are managed.\r\n<h4>Process limitations<\/h4>\r\n<p class=\"intro-box\">Traditional ETL tools often have a limited number of allowed processes for users.<\/p>\r\n\r\n<div class=\"white-box-col\">\r\n<div class=\"white-box-wrap\">\r\n<h2>Mistakes in ETL modernization<\/h2>\r\nOrganizations across various industries have already moved to ETL modernization. At Wavicle, we see various mistakes from strategy to implementation.\r\n<h4>Initial setup and scalability<\/h4>\r\n\u201cThe cloud does it all for us right?\u201d Eh, not so much. It still takes a tremendous amount of manual work to set up processes in the cloud for modern ETL platforms. Organizations often overlook the cost and bandwidth associated with building these processes. Beyond setup, we often see a lack of internal expertise and experience in how scalability works when it comes to modern ETL platforms and an organization\u2019s preferred cloud.\r\n<h4>Capabilities of the legacy platform<\/h4>\r\nIf not accounted for during an initial strategy phase, organizations can overlook capabilities that were widely used by their internal teams within their prior platform. This can stall the rapid utilization that is expected with a modern ETL platform.\r\n<h4>On-premises connectivity<\/h4>\r\nSome modern ETL tools do not support connectivity to on-premise systems at all. If this isn\u2019t accounted for and addressed, organizations can face a major ingestion challenge with their remaining on-premises systems.\r\n\r\n<\/div>\r\n<\/div>\r\n<!-- \/wp:post-content -->","protected":false},"excerpt":{"rendered":"<p>The cloud evolution is no longer a movement for modern business, it\u2019s an inescapable reality. A vastly greater amount of data sources, the volume of customer data, and disruptions to the supply chain call for companies to fully utilize the cloud and its unlimited compute and capacity. To keep up, organizations need real-time data processing&hellip; <a class=\"more-link\" href=\"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/blog\/etl-modernization-reduce-migration-timelines-and-unlock-scalabilty-and-real-time-data-processing\/\">Continue reading <span class=\"screen-reader-text\">ETL Modernization: Reduce Migration Timelines and Achieve Scalable, Real-Time Data Processing<\/span><\/a><\/p>\n","protected":false},"author":10,"featured_media":1071,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[10,11,50],"class_list":["post-315","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-augment","tag-aws","tag-wavicle-glue-converter","entry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>ETL Modernization for Faster Cloud Migration &amp; Scalability<\/title>\n<meta name=\"description\" content=\"Cut ETL migration timelines and enable real-time, scalable data processing with modern ETL platforms like AWS Glue.\" \/>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ETL Modernization for Faster Cloud Migration &amp; Scalability\" \/>\n<meta property=\"og:description\" content=\"Cut ETL migration timelines and enable real-time, scalable data processing with modern ETL platforms like AWS Glue.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/blog\/etl-modernization-reduce-migration-timelines-and-unlock-scalabilty-and-real-time-data-processing\/\" \/>\n<meta property=\"og:site_name\" content=\"Wavicle Data Solutions\" \/>\n<meta property=\"article:published_time\" content=\"2022-03-02T23:07:18+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-17T05:14:02+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/wp-content\/uploads\/2025\/09\/5491.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1276\" \/>\n\t<meta property=\"og:image:height\" content=\"1080\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Ranjith Ramachandran\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ranjith Ramachandran\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" 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