AWSSDK.Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. You can create and run an ETL job with a few clicks in the AWS Management Console. You simply point AWS Glue to your data stored on AWS, and AWS Glue discovers your data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, your data is immediately searchable, queryable, and available for ETL. AWS Glue generates the code to execute your data transformations and data loading processes. AWS Glue generates Python code that is entirely customizable, reusable, and portable. Once your ETL job is ready, you can schedule it to run on AWS Glue's fully managed, scale-out Spark environment. AWS Glue provides a flexible scheduler with dependency resolution, job monitoring, and alerting. AWS Glue is serverless, so there is no infrastructure to buy, set up, or manage. It automatically provisions the environment needed to complete the job, and customers pay only for the compute resources consumed while running ETL jobs. With AWS Glue, data can be available for analytics in minutes.
Install
dotnet add package AWSSDK.Glue --version 4.0.34
Install-Package AWSSDK.Glue -Version 4.0.34
<PackageReference Include="AWSSDK.Glue" Version="4.0.34" />
Frameworks
No framework metadata available.
Dependencies
Adoption guide
A verified publisher signal is available. Assess fit from the package's supported frameworks, license and dependency graph rather than popularity alone.
No target framework metadata is available. Confirm compatibility in a representative project before standardising on this package.
How to read this guidance
Sources: published NuGet v3 registry metadata and explicit NuBrowse editorial guides. Refresh: package metadata is refreshed from NuGet when the page loads. Limit: this is not a security, legal or compatibility guarantee; validate the selected version in your project.
Useful next steps
Move from package metadata to a concrete selection or review workflow.