FAQs On AWS Glue
1. AWS Data Catalog
A centralised metadata repository that houses information about your data from multiple data sources is the AWS Glue Data Catalogue. It offers a single interface for finding, comprehending, and managing your data assets. This catalogue is used by an AWS Glue ETL job during execution to comprehend data properties and guarantee proper transformation.
2. AWS DataBrew
AWS Glue data brew is an visual data preparation service with which we can get the clean data which can be used for the data analytics and machine learning purpose. You can also create and manage the data preparation workflows with the help of visual development of AWS glue databrew.
3. AWS Glue Studio
AWS Glue studio will helps you to visualize the data integration service that is ETL (extract,transform,load) with out writing the code you can just manage by using the drag and drop option.
4. AWS Glue Dynamic Frame
Working with big datasets in AWS Glue is made flexible and effective with the help of AWS Glue Dynamic Frame, a data representation tool.
5. AWS Glue Connectors
You can connect AWS Glue ETL jobs to a variety of data sources and destinations by using the pre-built connectors known as AWS Glue Connectors. These connectors offer a standardised method of interacting with various data sources and formats, making the process of extracting, transforming, and loading data easier.
6. AWS Glue API
You can automate and manage a number of AWS Glue features through the API, such as job execution, data catalogues, crawlers, and more.
Introduction To AWS Glue ETL
The Extract, Transform, Load(ETL) process has been designed specifically for the purpose of transferring data from its source database to the data warehouse. However, the challenges and complexities of ETL can make it hard to implement them successfully for all our enterprise data. For this reason, Amazon has introduced AWS Glue.
AWS Glue is a fully managed ETL(Extract, Transform, and Load) service that makes it simple and cost-effective to categorize our data, clean it, enrich it, and move it reliably between various data stores. It consists of a central metadata repository known as the AWS Glue data catalog an ETL engine that automatically generates Python code and a flexible scheduler that handles dependency resolution job monitoring. AWS Glue is serverless which means that there is no infrastructure to set or manage a setup.