Amazon Glue
Simple, scalable, and serverless data integration
Amazon Glue
Simple, scalable, and serverless data integration
Amazon Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. Amazon Glue provides all of the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months.
Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.
Amazon Glue provides both visual and code-based interfaces to make data integration easier. Users can easily find and access data using the Amazon Glue Data Catalog. Data engineers and ETL (extract, transform, and load) developers can create and run ETL workflows. Data analysts and data scientists can use Amazon Glue DataBrew to visually enrich, clean, and normalize data without writing code.
Amazon Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. Amazon Glue provides all of the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months.
Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.
Amazon Glue provides both visual and code-based interfaces to make data integration easier. Users can easily find and access data using the Amazon Glue Data Catalog. Data engineers and ETL (extract, transform, and load) developers can create and run ETL workflows. Data analysts and data scientists can use Amazon Glue DataBrew to visually enrich, clean, and normalize data without writing code.
Benefits
Faster Data Integration
No Servers to Manage
Automate Your Data Integration at Scale
Benefits
Faster Data Integration
No Servers to Manage
Automate Your Data Integration at Scale
How It Works
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Build Event-Driven ETL Pipelines
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Find Data Across Multiple Data Stores
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Self-Service Visual Data Preparation
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Build Event-Driven ETL Pipelines
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Amazon Glue can run your ETL jobs as new data arrives. For example, you can use an Amazon Lambda function to trigger your ETL jobs to run as soon as new data becomes available in Amazon S3. You can also register this new dataset in the Amazon Glue Data Catalog as part of your ETL jobs.
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Find Data Across Multiple Data Stores
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You can use the Amazon Glue Data Catalog to quickly discover and search across multiple Amazon data sets without moving the data. Once the data is cataloged, it is immediately available for search and query using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
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Self-Service Visual Data Preparation
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Amazon Glue DataBrew enables you to explore and experiment with data directly from your data lake, data warehouses, and databases, including Amazon S3, Amazon Redshift, Amazon Lake Formation, Amazon Aurora, and Amazon RDS. You can choose from over 250 prebuilt transformations in Amazon Glue DataBrew to automate data preparation tasks, such as filtering anomalies, standardizing formats, and correcting invalid values. After the data is prepared, you can immediately use it for analytics and machine learning. Learn more about Amazon Glue DataBrew here.
How It Works
-
Build Event-Driven ETL Pipelines
-
Find Data Across Multiple Data Stores
-
Self-Service Visual Data Preparation
-
Build Event-Driven ETL Pipelines
-
Amazon Glue can run your ETL jobs as new data arrives. For example, you can use an Amazon Lambda function to trigger your ETL jobs to run as soon as new data becomes available in Amazon S3. You can also register this new dataset in the Amazon Glue Data Catalog as part of your ETL jobs.
-
Find Data Across Multiple Data Stores
-
You can use the Amazon Glue Data Catalog to quickly discover and search across multiple Amazon data sets without moving the data. Once the data is cataloged, it is immediately available for search and query using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
-
Self-Service Visual Data Preparation
-
Amazon Glue DataBrew enables you to explore and experiment with data directly from your data lake, data warehouses, and databases, including Amazon S3, Amazon Redshift, Amazon Lake Formation, Amazon Aurora, and Amazon RDS. You can choose from over 250 prebuilt transformations in Amazon Glue DataBrew to automate data preparation tasks, such as filtering anomalies, standardizing formats, and correcting invalid values. After the data is prepared, you can immediately use it for analytics and machine learning. Learn more about Amazon Glue DataBrew here.
How to Get Started
Find out How It Works
Learn more about the key features of Amazon Glue.
Sign up for a Free Account
Pay nothing or try for free while learning the fundamentals and building on Amazon Web Services.
Connect With an Expert
From development to enterprise-level programs, get the right support at the right time.
How to Get Started
Find out How It Works
Learn more about the key features of Amazon Glue.
Sign up for a Free Account
Pay nothing or try for free while learning the fundamentals and building on Amazon Web Services.
Connect With an Expert
From development to enterprise-level programs, get the right support at the right time.
