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Average Ratings 0 Ratings
Description
Introducing a compact, edge-optimized SQL database engine that integrates artificial intelligence: Azure SQL Edge. This powerful Internet of Things (IoT) database is specifically designed for edge computing, offering features like data streaming and time series analysis alongside in-database machine learning and graph capabilities. By extending the highly regarded Microsoft SQL engine to edge devices, it ensures uniform performance and security across your entire data infrastructure, whether in the cloud or at the edge. You can create your applications once and deploy them seamlessly across various environments, including edge locations, on-premises data centers, or Azure. With integrated data streaming and time series functionalities, along with advanced analytics powered by machine learning and graph features, users benefit from low-latency performance. It enables efficient data processing at the edge, accommodating online, offline, or hybrid scenarios to address challenges related to latency and bandwidth. Updates and deployments can be managed easily via the Azure portal or your organization’s portal, ensuring consistent security and streamlined operations. Furthermore, leverage the built-in machine learning capabilities to detect anomalies and implement business logic directly at the edge, enhancing real-time decision-making and operational efficiency. This comprehensive solution empowers organizations to harness the full potential of their data, regardless of its location.
Description
Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.
API Access
Has API
API Access
Has API
Integrations
Microsoft Azure
Advanced Query Tool (AQT)
Amazon S3
Amazon Web Services (AWS)
Azure Marketplace
Azure SQL Database
Coginiti
Datametica
Digna
EHSwise
Integrations
Microsoft Azure
Advanced Query Tool (AQT)
Amazon S3
Amazon Web Services (AWS)
Azure Marketplace
Azure SQL Database
Coginiti
Datametica
Digna
EHSwise
Pricing Details
$60 per year
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/products/azure-sql/edge/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/netezza
Product Features
SQL Server
CPU Monitoring
Credential Management
Database Servers
Deployment Testing
Docker Compatible Containers
Event Logs
History Tracking
Patch Management
Scheduling
Supports Database Clones
User Activity Monitoring
Virtual Machine Monitoring
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge