Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Yes
API Access
Has API
No
Integrations
C
Yes
C++
Yes
Capgemini Intelligent Automation Platform
No
DataTerrain
No
HPE Consumption Analytics
No
Kubernetes
Yes
NVIDIA Jetson
Yes
NVIDIA Metropolis
Yes
NVIDIA TensorRT
Yes
NVIDIA Triton Inference Server
Yes
Integrations
C
No
C++
No
Capgemini Intelligent Automation Platform
Yes
DataTerrain
Yes
HPE Consumption Analytics
Yes
Kubernetes
No
NVIDIA Jetson
No
NVIDIA Metropolis
No
NVIDIA TensorRT
No
NVIDIA Triton Inference Server
No
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
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
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
Yes
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
Yes
Live Training (Online)
Yes
In Person
Yes
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
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
Product Features
IoT
Application Development
No
Big Data Analytics
Yes
Configuration Management
No
Connectivity Management
No
Data Collection
Yes
Data Management
Yes
Device Management
No
Performance Management
No
Prototyping
No
Visualization
Yes
IoT Analytics
Activity Dashboard
No
Activity Tracking
No
Analytics
No
Asset Tracking
No
Data Collection
No
Data Synchronization
No
Data Visualization
No
ETL
No
Multiple Data Sources
No
Performance Analysis
No
Real-Time Analytics
No
Real-Time Data
No
Real-Time Monitoring
No
Status Tracking
No