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Average Ratings 0 Ratings
Description
AWS DataSync is a secure online solution designed to automate and speed up the transfer of data from on-premises storage to AWS Storage services. This service streamlines migration planning while significantly lowering the costs associated with on-premises data transfer through its fully managed architecture that can effortlessly adapt to increasing data volumes. It enables users to transfer data between various systems, including Network File System (NFS) shares, Server Message Block (SMB) shares, Hadoop Distributed File Systems (HDFS), self-managed object storage, as well as multiple AWS services such as AWS Snowcone, Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), and several Amazon FSx file systems. Moreover, DataSync facilitates the movement of data not only between AWS and on-premises environments but also across different public clouds, simplifying processes for replication, archiving, and data sharing for applications. With its robust end-to-end security measures, including data encryption and integrity checks, DataSync ensures that data remains protected throughout the transfer process, allowing businesses to focus on their core operations without worrying about data security. This comprehensive solution is ideal for organizations looking to enhance their data management capabilities in the cloud.
Description
Effortlessly synchronize on-premises asset files with Amazon Simple Storage Service (S3) to guarantee cloud availability. Connect seamlessly with local servers, oversee data transfers prior to the rendering process, and categorize accounts and instances for precise billing. Acquire software licenses based on usage, utilize your own licenses, or combine both approaches to develop third-party digital content. Take advantage of Amazon Elastic Compute Cloud (EC2) Spot Instances to achieve savings of up to 90% compared to traditional on-demand pricing. Establish a render farm in just a few minutes, allowing for the execution of multiple projects simultaneously while enhancing cost management. Create either a hybrid or cloud-centric render farm that can scale to thousands of cores in mere minutes through the AWS Portal. Construct, customize, and implement render farms using the Render Farm Deployment Kit (RFDK) in well-known programming languages like Python. Employ the Jigsaw tool to accelerate the rendering of ultra-high-resolution images by distributing the workload across numerous machines, significantly improving efficiency. This integrated approach not only simplifies the rendering process but also optimizes resource utilization and cost-effectiveness.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
AWS Marketplace
No
AWS Storage Gateway
Yes
AWS Thinkbox Sequoia
No
Amazon EC2
No
Amazon FSx
Yes
Amazon FSx for Lustre
Yes
Amazon S3 Glacier
Yes
Hadoop
Yes
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
AWS Marketplace
Yes
AWS Storage Gateway
No
AWS Thinkbox Sequoia
Yes
Amazon EC2
Yes
Amazon FSx
No
Amazon FSx for Lustre
No
Amazon S3 Glacier
No
Hadoop
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/datasync/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/thinkbox-deadline/