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ease
features
design
support

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Description

NVIDIA's DeepStream SDK serves as a robust toolkit for streaming analytics, leveraging GStreamer to facilitate AI-driven processing across various sensors, including video, audio, and image data. It empowers developers to craft intricate stream-processing pipelines that seamlessly integrate neural networks alongside advanced functionalities like tracking, video encoding and decoding, as well as rendering, thereby enabling real-time analysis of diverse data formats. DeepStream plays a crucial role within NVIDIA Metropolis, a comprehensive platform aimed at converting pixel and sensor information into practical insights. This SDK presents a versatile and dynamic environment catered to multiple sectors, offering support for an array of programming languages such as C/C++, Python, and an easy-to-use UI through Graph Composer. By enabling real-time comprehension of complex, multi-modal sensor information at the edge, it enhances operational efficiency while also providing managed AI services that can be deployed in cloud-native containers managed by Kubernetes. As industries increasingly rely on AI for decision-making, DeepStream's capabilities become even more vital in unlocking the value embedded within sensor data.

Description

Utilize a comprehensive, AI-integrated solution to access, organize, select, and transform data from the Internet of Things. SAS Analytics for IoT encompasses the entire analytics life cycle related to IoT, featuring a streamlined and extensible ETL process, a data model focused on sensors, and an advanced analytics framework supported by a premier streaming execution engine that facilitates complex multi-phase analytics. Powered by SAS® Viya®, this solution operates efficiently within a fast, in-memory distributed setting. Discover how to create SAS Event Stream Processing applications capable of handling high-volume and high-velocity data streams, delivering real-time responses while retaining only the essential data elements. This course introduces fundamental principles of event stream processing, detailing the various component objects that can be utilized to construct effective event stream processing applications. Our commitment to curiosity drives innovation, as SAS analytics solutions convert raw data into actionable insights, empowering customers globally to embark on bold new ventures that foster advancement. Embrace the future of data analytics and unlock limitless possibilities with SAS.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C
C++
Capgemini Intelligent Automation Platform
DataTerrain
HPE Consumption Analytics
Helm
Kubernetes
NVIDIA Jetson
NVIDIA Metropolis
NVIDIA TensorRT
NVMesh
Omnio
Phonexia Voice Inspector
PyTorch
Python
SAS Data Loader for Hadoop
SAS Visual Statistics
SAS Viya
TensorFlow
Uptempo

Integrations

C
C++
Capgemini Intelligent Automation Platform
DataTerrain
HPE Consumption Analytics
Helm
Kubernetes
NVIDIA Jetson
NVIDIA Metropolis
NVIDIA TensorRT
NVMesh
Omnio
Phonexia Voice Inspector
PyTorch
Python
SAS Data Loader for Hadoop
SAS Visual Statistics
SAS Viya
TensorFlow
Uptempo

Pricing Details

No price information available.
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

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/deepstream-sdk

Vendor Details

Company Name

SAS Institute

Country

United States

Website

support.sas.com/en/software/analytics-for-iot-support.html

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Product Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Alternatives

Alternatives