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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.

What is AWS Batch?

AWS Batch offers a convenient and efficient platform for developers, scientists, and engineers to manage a large number of batch computing tasks within the AWS ecosystem. It automatically determines the optimal amount and type of computing resources, such as CPU- or memory-optimized instances, based on the specific requirements and scale of the submitted jobs. This functionality allows users to avoid the difficulties of installing or maintaining batch computing software and server infrastructure, enabling them to focus on analyzing results and solving problems. With the ability to plan, schedule, and execute batch workloads, AWS Batch utilizes the full range of AWS compute services, including AWS Fargate, Amazon EC2, and Spot Instances. Notably, AWS Batch does not impose any additional charges; users are only billed for the AWS resources they use, such as EC2 instances or Fargate tasks, to run and store their batch jobs. This smart resource allocation not only conserves time but also minimizes operational burdens for organizations, fostering greater productivity and efficiency in their computing processes. Ultimately, AWS Batch empowers users to harness cloud computing capabilities without the typical hassles of resource management.

Media

Media

Integrations Supported

Amazon EC2
EC2 Spot
AWS App Mesh
AWS Fargate
AWS ParallelCluster
AWS Secrets Manager
AWS Step Functions
Amazon DynamoDB
Amazon EC2 Trn2 Instances
Amazon EMR
Amazon FSx for Lustre
Amazon Linux 2
Amazon S3
BMC AMI Ops Automation for Capping
Beats
Functionize
RadiantOne
Saagie
Stonebranch
Union Cloud

Integrations Supported

Amazon EC2
EC2 Spot
AWS App Mesh
AWS Fargate
AWS ParallelCluster
AWS Secrets Manager
AWS Step Functions
Amazon DynamoDB
Amazon EC2 Trn2 Instances
Amazon EMR
Amazon FSx for Lustre
Amazon Linux 2
Amazon S3
BMC AMI Ops Automation for Capping
Beats
Functionize
RadiantOne
Saagie
Stonebranch
Union Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

$1 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/datapipeline/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/batch/

Categories and Features

ETL

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

Categories and Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

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