AWS Glue vs Azure Data Factory скачать в хорошем качестве

AWS Glue vs Azure Data Factory

Are you drowning in data? 🌊 Deciding between AWS Glue and Azure Data Factory (ADF) can be a heavyweight battle for any organization. In this video, we break down the core philosophies, features, and pricing of these two cloud ETL giants to help you pick the perfect champion for your data pipeline! 🕒 Timestamps: [00:00:10] Intro: The importance of ETL (Extract, Transform, Load) in the cloud. [00:01:03] AWS Glue: The "Smart Assistant" – Serverless, automated, and powered by Apache Spark. [00:01:31] Azure Data Factory: The "Customizable Assembly Line" – Visual orchestration and massive connectivity. [00:02:11] Feature Face-Off: Code-heavy (Python/Scala) vs. No-code friendly interfaces. [00:02:38] Ecosystem & Connectivity: 60+ vs. 90+ connectors and hybrid cloud support. [00:03:09] Flexibility: The game-changer of native SSIS support in ADF. [00:03:39] The Price of Victory: DPU-hours vs. Granular, multi-faceted pricing models. [00:04:47] Summary: How to choose based on your team’s skills and existing infrastructure. 💡 Key Takeaways: Choose AWS Glue if: You are deep in the AWS ecosystem, have a team of Python/Scala developers, and need the raw power of a serverless Spark engine for data lakes. 🛠️ Choose Azure Data Factory if: Your world revolves around Microsoft and Azure, you need a visual low-code tool, or you are migrating legacy SSIS packages to the cloud. 🏗️ 📊 Community Ratings: Both platforms are highly rated by users (Gartner), with ADF holding a slight edge in maturity and user-friendliness. 🌟 #AWSGlue #AzureDataFactory #CloudComputing #ETL #DataEngineering #BigData #AWS vs #Azure