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Description

AWS Outposts is a comprehensive managed service that extends the capabilities of AWS infrastructure, services, APIs, and tools to nearly any data center, co-location site, or on-premises environment, ensuring a seamless hybrid cloud experience. It excels for workloads that necessitate low-latency connectivity to local systems, on-site data processing, data residency compliance, and the migration of applications with dependencies on local resources. With AWS compute, storage, database, and additional services operating locally on Outposts, users can utilize the complete suite of AWS offerings available in their specified Region to develop, oversee, and scale their on-premises applications with the familiar AWS ecosystem. Additionally, there is an upcoming VMware variant of AWS Outposts, which will provide a fully managed VMware Software-Defined Data Center (SDDC) operating on the AWS Outposts infrastructure in customer environments. This enhancement aims to further integrate VMware’s capabilities with AWS, allowing organizations to leverage both platforms efficiently.

Description

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS App Mesh Yes 
New Relic Yes 
AWS Data Pipeline No 
Amazon S3 Express One Zone No 
Amazon SageMaker Unified Studio No 
Apache Hive No 
Ataccama ONE No 
Cloudian Yes 
Hadoop No 
Okera No 
Pelanor No 
Progress DataDirect No 
Quorso No 
SAS Studio No 
Service Center No 
Sifflet No 
Tonic Ephemeral No 
TrustLogix No 
Veeam Backup for AWS Yes 
Veza No 

Integrations

AWS App Mesh Yes 
New Relic Yes 
AWS Data Pipeline Yes 
Amazon S3 Express One Zone Yes 
Amazon SageMaker Unified Studio Yes 
Apache Hive Yes 
Ataccama ONE Yes 
Cloudian No 
Hadoop Yes 
Okera Yes 
Pelanor Yes 
Progress DataDirect Yes 
Quorso Yes 
SAS Studio Yes 
Service Center Yes 
Sifflet Yes 
Tonic Ephemeral Yes 
TrustLogix Yes 
Veeam Backup for AWS No 
Veza Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
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) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
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 No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/outposts/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/emr/

Product Features

Cloud Management

Access Control No 
Billing & Provisioning No 
Capacity Analytics No 
Cost Management No 
Demand Monitoring No 
Multi-Cloud Management No 
Performance Analytics No 
SLA Management No 
Supply Monitoring No 
Workflow Approval No 

Data Center Management

Audit Trail No 
Behavior-Based Acceleration No 
Cross Reference System No 
Device Auto Discovery No 
Diagnostic Testing No 
Import / Export Data No 
JCL Management No 
Multi-Platform No 
Multi-User No 
Power Management No 
Sarbanes-Oxley Compliance No 

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

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