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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 Auto Scaling?

AWS Auto Scaling is a service that consistently observes your applications and automatically modifies resource capacity to maintain steady performance while reducing expenses. This platform facilitates rapid and simple scaling of applications across multiple resources and services within a matter of minutes. It boasts a user-friendly interface that allows users to develop scaling plans for various resources, such as Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. By providing customized recommendations, AWS Auto Scaling simplifies the task of enhancing both performance and cost-effectiveness, allowing users to strike a balance between the two. Additionally, if you are employing Amazon EC2 Auto Scaling for your EC2 instances, you can effortlessly integrate it with AWS Auto Scaling to broaden scalability across other AWS services. This integration guarantees that your applications are always provisioned with the necessary resources exactly when required. Ultimately, AWS Auto Scaling enables developers to prioritize the creation of their applications without the burden of managing infrastructure requirements, thus fostering innovation and efficiency in their projects. By minimizing operational complexities, it allows teams to focus more on delivering value and enhancing user experiences.

Media

Media

Integrations Supported

Amazon DynamoDB
Amazon EC2
EC2 Spot
AWS App Mesh
Amazon Aurora
Amazon CloudWatch
Amazon EMR
Amazon Fresh
Amazon Web Services (AWS)
Beats
Ease Stream
Functionize
Jeeva eClinical Cloud
New Relic
Observe
RadiantOne
SquaredUp
Suntek Reporting
Sweven
WebLOAD

Integrations Supported

Amazon DynamoDB
Amazon EC2
EC2 Spot
AWS App Mesh
Amazon Aurora
Amazon CloudWatch
Amazon EMR
Amazon Fresh
Amazon Web Services (AWS)
Beats
Ease Stream
Functionize
Jeeva eClinical Cloud
New Relic
Observe
RadiantOne
SquaredUp
Suntek Reporting
Sweven
WebLOAD

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/autoscaling/

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

Server Management

CPU Monitoring
Credential Management
Database Servers
Email Monitoring
Event Logs
History Tracking
Patch Management
Scheduling
User Activity Monitoring
Virtual Machine Monitoring

Server Virtualization

Audit Management
Health Monitoring
Live Machine Migration
Multi-OS Virtual Machines
Patching / Backup
Performance Log
Performance Optimization
Rapid Provisioning
Security Management
Type 1 / Type 2 Hypervisor

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