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What is AWS DataSync?
AWS DataSync is a powerful online service designed to enhance and automate the transfer of data between on-premises storage systems and AWS Storage solutions. By optimizing the migration procedure, it effectively reduces costly data transfer expenses associated with on-premises systems while providing a fully managed service that can easily scale to accommodate growing data requirements. This tool supports data transfers across a variety of platforms, such as Network File System (NFS) shares, Server Message Block (SMB) shares, Hadoop Distributed File Systems (HDFS), self-managed object storage, AWS Snowcone, and various Amazon services including Amazon Simple Storage Service (S3) buckets, Amazon Elastic File System (EFS), and numerous Amazon FSx configurations. Additionally, DataSync simplifies data movement between other public cloud providers and AWS Storage services, enabling straightforward replication, archiving, or sharing of application data. It guarantees thorough security throughout the transfer process, integrating features like data encryption and integrity verification for every file moved. Overall, AWS DataSync is not just a tool; it is an essential asset for organizations aiming to enhance their cloud data management strategies while ensuring security and efficiency. This positions it as a critical component in the modern data landscape.
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.
Integrations Supported
Amazon S3
AWS App Mesh
AWS Storage Gateway
Amazon DynamoDB
Amazon EC2
Amazon EMR
Amazon FSx
Amazon FSx for Lustre
Amazon RDS
Amazon S3 Glacier
Integrations Supported
Amazon S3
AWS App Mesh
AWS Storage Gateway
Amazon DynamoDB
Amazon EC2
Amazon EMR
Amazon FSx
Amazon FSx for Lustre
Amazon RDS
Amazon S3 Glacier
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$1 per month
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/datasync/
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/datapipeline/
Categories and Features
Categories and Features
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control