What is AWS Glue?
Analytics users can easily find, prepare, transport, and combine data from many sources with the help of AWS Glue, a serverless data integration tool. It may be applied to application development, analytics, and machine learning. Additional productivity and data operations tools for creating, executing tasks, and putting business procedures into practice are also included.
You can manage your data in a centralized data catalogue and find and connect to over 70 different data sources using AWS Glue. To load data into your data lakes, you can easily design, execute, and track extract, transform, and load (ETL) pipelines. Additionally, you may use Amazon Redshift Spectrum, Amazon EMR, and Amazon Athena to search and query catalogued data right now.
It combines major data integration functionalities. These include of centralised cataloguing, data discovery, contemporary ETL, cleansing, and transformation. Additionally, it is serverless, meaning that no infrastructure has to be maintained. It provides a wide range of workloads and user types with its flexible support for all workloads, including ETL, ELT, and streaming, in a single service.
Additionally, integrating data throughout your architecture is made simple with AWS Glue. It connects to Amazon S3 data lakes and AWS analytics services. All users, from developers to business users, may easily utilize AWS Glue‘s integration interfaces and job-authoring tools, which offer customized solutions for a range of technical skill levels.
It enables you concentrate on high-value tasks that optimize the value of your data by scaling on demand. All data formats and schema variations are supported, and it scalable for any quantity of data. AWS Glue offers pay-as-you-go pricing and built-in high availability to boost agility and save expenses.
How AWS Glue Operates
It orchestrates your ETL (extract, transform, and load) activities to create output streams, data lakes, and warehouses using other AWS services. In order to convert your data, generate runtime logs, save your job logic, and provide notifications to assist you in keeping an eye on your task runs, AWS Glue invokes API actions.
You may concentrate on developing and overseeing your ETL work by connecting these services into a managed application using the it interface. The console handles job development and administrative tasks for you. For it to access your data sources and publish to your data targets, you need credentials and other attributes.
The resources needed to operate your workload are provisioned and managed by AWS Glue. It handles the infrastructure creation for ETL tools, saving you the trouble. When resources are needed, AWS Glue runs your workload on an instance from its warm pool of instances to speed up starting.
You use table definitions in your Data Catalogue to construct tasks using AWS Glue. Jobs are made up of scripts with instructions on how to carry out the appropriate data transformation operations. You choose which source data fills your target and where your target data is located. It converts your data from the source format to the destination format based on your inputs. As an alternative, you may use the AWS Glue interface or API to write custom scripts that will handle your data in accordance with your unique needs.
Why Use Glue?
Crawlers (which find data) and extract, transform, and load (ETL) tasks (which process and load data) are invoiced on an hourly basis with it. You pay a simple monthly price to store and retrieve the metadata for the AWS Glue Data Catalogue. Both the first million accesses and the first million items saved are free. You pay an hourly cost, measured in seconds, if you supply a development endpoint to develop your ETL code interactively.
Interactive sessions are charged by the session for AWS Glue DataBrew, whereas DataBrew tasks are charged by the minute. There is no additional fee to use the AWS Glue Schema Registry.
