Here is a detailed comparison between AWS Data Pipeline, AWS Glue & AWS Lambda understand who is the clear winner
Join the DZone community and get the full member experience. AWS provides users with some of the most effective ETL tools for streamlined data management. Whether you are willing to implement a new platform, undertake third-party integrations, or simply move all your data to a warehouse, these ETL tools help you in managing your database in a secure and private manner. However, it is important to select the right ETL tool for AWS depending on your specific requirements. Here, we would compare three of such tools – AWS Data Pipeline, AWS Glue, and AWS Lambda. AWS Data Pipeline is an ETL tool by Amazon that helps users automate data transfer processes. It helps you move data through dedicated and automated workflows that make data tasks dependent on the tasks completed successfully earlier. The AWS Data Pipeline workflows allow users to automate and leverage their ETL processes on the AWS cloud, making them take an advantage of the features already existing on the platform. Moreover, the tool is suitable for both technical and non-technical users as it provides you with a simple drag-and-drop interface. This allows users to have complete control of specific computational resources pertaining to the Data Pipeline logic. The aim of AWS Data Pipeline is to automate seamless data movement within the AWS cloud by defining, scheduling, and automating individual tasks. For example, if a user is willing to extract event data from a specific source on a regular basis, they can do so by designing a data pipeline and running the same on an Amazon EMR over the concerned datasets for generating extensive reports. AWS Data Pipeline makes data management easier as it allows users to transfer and transform their datasets across different AWS tools and monitor all relevant processes from a centralized location. Here are some of the most important features of AWS Data Pipeline: • The tool makes it easy for users to debug or change the logic of your automated data workflow by providing complete control to compute resources required to execute business logic. • The tool provides users with an architecture that is high on flexibility and tolerance.
