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What is AWS Glue?

AWS Glue is a fully managed, serverless solution tailored for data integration, facilitating the easy discovery, preparation, and merging of data for a variety of applications, including analytics, machine learning, and software development. The service incorporates all essential functionalities for effective data integration, allowing users to conduct data analysis and utilize insights in a matter of minutes, significantly reducing the timeline from months to mere moments. The data integration workflow comprises several stages, such as identifying and extracting data from multiple sources, followed by the processes of enhancing, cleaning, normalizing, and merging the data before it is systematically organized in databases, data warehouses, and data lakes. Various users, each with their specific tools, typically oversee these distinct responsibilities, ensuring a comprehensive approach to data management. By operating within a serverless framework, AWS Glue removes the burden of infrastructure management from its users, as it automatically provisions, configures, and scales the necessary resources for executing data integration tasks. This feature allows organizations to concentrate on gleaning insights from their data instead of grappling with operational challenges. In addition to streamlining data workflows, AWS Glue also fosters collaboration and productivity among teams, enabling businesses to respond swiftly to changing data needs. The overall efficiency gained through this service positions companies to thrive in today’s data-driven environment.

What is AWS Data Pipeline?

AWS Data Pipeline is a cloud service designed to facilitate the dependable transfer and processing of data between various AWS computing and storage platforms, as well as on-premises data sources, following established schedules. By leveraging AWS Data Pipeline, users gain consistent access to their stored information, enabling them to conduct extensive transformations and processing while effortlessly transferring results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. This service greatly simplifies the setup of complex data processing tasks that are resilient, repeatable, and highly dependable. Users benefit from the assurance that they do not have to worry about managing resource availability, inter-task dependencies, transient failures, or timeouts, nor do they need to implement a system for failure notifications. Additionally, AWS Data Pipeline allows users to efficiently transfer and process data that was previously locked away in on-premises data silos, which significantly boosts overall data accessibility and utility. By enhancing the workflow, this service not only makes data handling more efficient but also encourages better decision-making through improved data visibility. The result is a more streamlined and effective approach to managing data in the cloud.

Media

Media

Integrations Supported

AWS App Mesh
Amazon EC2
Amazon RDS
Amazon S3
Alex Solutions
Amazon DataZone
Amazon S3 Express One Zone
Amazon SageMaker Unified Studio
Amundsen
New Relic
OpenAccess SDK
Privacera
Progress DataDirect
Saagie
Varada
Wavo
kPow

Integrations Supported

AWS App Mesh
Amazon EC2
Amazon RDS
Amazon S3
Amazon DynamoDB
Amazon EMR
Mobito

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$1 per month
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/glue/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/datapipeline/

Categories and Features

Data Catalog

Not specified

Data Discovery

Not specified

Data Integration

Not specified

Data Preparation

Not specified

Data Virtualization

Not specified

ETL

Data Analysis
Data Filtering
Data Quality Control
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

Data Pipeline

Not specified

ETL

Not specified

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