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ease
features
design
support

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Description

Amazon EC2 Inf1 instances are specifically designed to provide efficient, high-performance machine learning inference at a competitive cost. They offer an impressive throughput that is up to 2.3 times greater and a cost that is up to 70% lower per inference compared to other EC2 offerings. Equipped with up to 16 AWS Inferentia chips—custom ML inference accelerators developed by AWS—these instances also incorporate 2nd generation Intel Xeon Scalable processors and boast networking bandwidth of up to 100 Gbps, making them suitable for large-scale machine learning applications. Inf1 instances are particularly well-suited for a variety of applications, including search engines, recommendation systems, computer vision, speech recognition, natural language processing, personalization, and fraud detection. Developers have the advantage of deploying their ML models on Inf1 instances through the AWS Neuron SDK, which is compatible with widely-used ML frameworks such as TensorFlow, PyTorch, and Apache MXNet, enabling a smooth transition with minimal adjustments to existing code. This makes Inf1 instances not only powerful but also user-friendly for developers looking to optimize their machine learning workloads. The combination of advanced hardware and software support makes them a compelling choice for enterprises aiming to enhance their AI capabilities.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS App Mesh
AWS Step Functions
AWS Trainium
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon S3 Express One Zone
Amazon SageMaker Studio
Amazon Web Services (AWS)
Apache Hive
Data Virtuality
EC2 Spot
Gurucul
Immuta
MXNet
Okera
Pelanor
Progress DataDirect
Quorso
Unravel
Veza

Integrations

AWS App Mesh
AWS Step Functions
AWS Trainium
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon S3 Express One Zone
Amazon SageMaker Studio
Amazon Web Services (AWS)
Apache Hive
Data Virtuality
EC2 Spot
Gurucul
Immuta
MXNet
Okera
Pelanor
Progress DataDirect
Quorso
Unravel
Veza

Pricing Details

$0.228 per hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/ec2/instance-types/inf1/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/emr/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Big Data

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

Alternatives

Alternatives

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