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What is Red Hat JBoss Data Virtualization?

Red Hat JBoss Data Virtualization is a powerful tool for virtual data integration, allowing users to unlock and present otherwise inaccessible data in a cohesive and accessible format that can be easily utilized. This solution aggregates data from diverse sources, such as various databases, XML files, and Hadoop systems, presenting them as a unified set of tables within a local database environment. It enables real-time, standards-compliant read and write access to a range of heterogeneous data repositories, enhancing efficiency. By simplifying the process of accessing distributed data, it significantly speeds up both application development and integration efforts. Users are empowered to customize and harmonize data semantics to fit the unique needs of different data consumers. Additionally, the system provides centralized management for access control along with comprehensive auditing capabilities through its robust security framework. Consequently, fragmented data can be swiftly converted into actionable insights, addressing the evolving demands of modern businesses. Furthermore, Red Hat ensures ongoing support and maintenance for its JBoss products throughout designated periods, allowing users to benefit from the latest updates and assistance, thereby enhancing overall operational effectiveness. This commitment to user support reinforces the reliability of the solution in a rapidly changing data landscape.

What is DataCurrent?

The real-time observation of rainfall using rain gauges allows operations teams to swiftly recognize possible flooding or sewer overflow incidents. By meticulously monitoring and analyzing precipitation levels across multiple locations, one can estimate rainfall in regions that lack direct measurement, employing the technique known as “Distributed Rainfall Modelling Technique” (DRMT). Moreover, merging rainfall radar data with rain gauge measurements enhances the creation of detailed rainfall coverage maps. Analyzing historical rainfall statistics also aids in developing rainfall intensity-duration curves, which can be matched against the region's design intensity-duration-frequency curves, facilitating the determination of return periods for significant events through forensic examination. Additionally, new intensity-duration-frequency curves can be established, influencing the design of essential drainage infrastructure such as sewers, channels, and storage systems. The ongoing analysis of flow data, in conjunction with rainfall information, leads to the formation of rainfall versus stormwater runoff response curves, which play a crucial role in accurately calibrating drainage models. This thorough methodology guarantees that urban planning and flood management initiatives are not only informed but also adapt effectively to real-time environmental conditions, ultimately enhancing community resilience to extreme weather events.

Media

Media

Integrations Supported

Azure Marketplace
Hadoop
WebLOAD

Integrations Supported

Azure Marketplace
Hadoop
WebLOAD

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Red Hat

Date Founded

1993

Company Location

United States

Company Website

access.redhat.com/products/red-hat-jboss-data-virtualization

Company Facts

Organization Name

Smart City Water

Company Location

Canada

Company Website

smartcitywater.ca/datacurrent/

Categories and Features

Categories and Features

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