Unlock your Red Hat JBoss Data Grid data with Red Hat JBoss Data Virtualization

Welcome to another episode of the series: “Unlock your Red Hat JBoss Data Grid (JDG) data with Red Hat JBoss Data Virtualization (JDV).”

This post will guide you through an example of connecting to Red Hat JBoss Data Grid data source, using Teiid Designer. In this example, we will demonstrate connecting to a local JDG data source.  We’re using the JDG 6.6.1, but you can connect to any local or remote JDG source (version 6.6.1) if you wish, using the same steps.

Continue reading “Unlock your Red Hat JBoss Data Grid data with Red Hat JBoss Data Virtualization”


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Red Hat JBoss Data Virtualization on OpenShift: Part 4 – Bringing data from outside to inside the PaaS

Welcome to part 4 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 4 – Bringing data from outside to inside the PaaS”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Red Hat JBoss Data Virtualization on OpenShift: Part 3 – Data federation

Welcome to part 3 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

When deployed on OpenShift, JDV enables:

  1. Service enabling your data
  2. Bringing data from outside to inside the PaaS
  3. Breaking up monolithic data sources virtually for a microservices architecture

Together with the JDV for OpenShift image, we have made available several OpenShift templates that allow you to test and bootstrap JDV.

Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 3 – Data federation”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Red Hat JBoss Data Virtualization on OpenShift: Part 2 – Service enable your data

Welcome to the part 2 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

When deployed on OpenShift, JDV enables:

  1. Service enabling your data
  2. Bringing data from outside to inside the PaaS
  3. Breaking up monolithic data sources virtually for a microservices architecture

Together with the JDV for OpenShift image, we have made available OpenShift templates that allow you to test and bootstrap JDV.

Introduction

In part 1 we described how to get started with JDV running on OpenShift. During the build phase of the pod several artifacts were downloaded from the provided GitHub URL in the JDV OpenShift template. We deployed two virtual databases (VDBs) called country-ws (external web service-based datasource) and marketdata-file (file-based datasource).

Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 2 – Service enable your data”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Red Hat JBoss Data Virtualization on OpenShift: Part 1 – Getting started

Red Hat JBoss Data Virtualization (JDV) is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

When deployed on OpenShift, JDV enables:

  1. Service enabling your data
  2. Bringing data from outside to inside the PaaS
  3. Breaking up monolithic data sources virtually for a microservices architecture

Together with the JDV for OpenShift image, we have made available OpenShift templates that allow you to test and bootstrap JDV.

This article will demonstrate how to get started with JDV running on OpenShift. JDV is available as a containerized xPaaS image that is designed for use with OpenShift Enterprise 3.2 and later. We’ll be using the Red Hat Container Development Kit (CDK) to get started quickly.

The CDK provides a pre-built CDK based on Red Hat Enterprise Linux to help you develop container-based (sometimes called docker) applications quickly. The containers you build can be easily deployed on any Red Hat container host or platform, including: Red Hat Enterprise Linux, Red Hat Enterprise Linux Atomic Host, and our platform-as-a-service solution, OpenShift Enterprise 3.

Prerequisites

Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 1 – Getting started”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Announcement: Red Hat JBoss Data Virtualization on OpenShift now available

We are happy to announce the availability of Red Hat JBoss Data Virtualization (JDV) 6.3 image running on OpenShift.

jdvose

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

When deployed on OpenShift, JDV enables:

Continue reading “Announcement: Red Hat JBoss Data Virtualization on OpenShift now available”


Join Red Hat Developers, a developer program for you to learn, share, and code faster – and get access to Red Hat software for your development.  The developer program and software are both free!

 


For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Unlock your Hadoop data with Hortonworks and Red Hat JBoss Data Virtualization

Welcome to this first episode of this series: “Unlock your [….] data with Red Hat JBoss Data Virtualization (JDV).”

This post will guide you through an example of connecting to a Hadoop source via the Hive2 driver, using Teiid Designer. In this example we will demonstrate connection to a local Hadoop source.  We’re using the Hortonworks 2.5 Sandbox running in Virtual Box for our source, but you can connect to another Hortonwork source if you wish using the same steps.

Hortonworks provides Hive JDBC and ODBC drivers that let you connect popular tools to query, analyze and visualize data stored within the Hortonworks Data Platform (HDP).

Note: we support HBase as well, stay tuned for an episode of Unlock your HBase data with Hortonworks and JDV.

Continue reading “Unlock your Hadoop data with Hortonworks and Red Hat JBoss Data Virtualization”


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Red Hat JBoss Data Virtualization 6.3 wins Database Trends and Applications Reader Choice 2016 Award for Best Data Virtualization Solution.

dbta

Database Trends and Applications magazine (DBTA) announced its 2016 Readers’ Choice Award winners recently, and Red Hat JBoss Data Virtualization was named winner in the category Best Data Virtualization Solution.  Furthermore, Red Hat was among the DBTA 100 list of companies that matter in data, compelling us to pause and reflect on the market changes taking place.

Continue reading “Red Hat JBoss Data Virtualization 6.3 wins Database Trends and Applications Reader Choice 2016 Award for Best Data Virtualization Solution.”

Announcing Red Hat JBoss Data Grid 7

We are very excited to announce General Availability (GA) of Red Hat JBoss Data Grid (JDG) 7!

JDG supercharges today’s modern applications and allows developers to meet tough requirements of high performance, availability, reliability, and elastic scale. JBoss Data Grid is compatible with the existing data tier as well as applications written in any language, using any framework and any platform via multiple APIs such as memcached, HotRod, and REST. Red Hat JBoss Data Grid empowers developers to obtain a streamlined approach to standing up new applications, avoiding the challenges normally associated with integrating applications and traditional databases.

JDG 7 introduces the following major new features:

Real-time Data Analytics

  • Distributed Streams
    JDG 7 introduces a distributed version of the Java 8 Stream API which enables you to perform rich analytics operations on data stored in JDG using the functional expressions available in the Stream API.
  • Apache Spark integration
    JDG 7 introduces a Resilient Distributed Dataset (RDD) and Discretized Stream (DStream) integration with Apache Spark version 1.6. This enables you to use JDG as a highly scalable, high-performance data source for Apache Spark, executing Spark and Spark Streaming operations on data stored in JDG.
  • Apache Hadoop Integration
    JDG 7 features a Hadoop InputFormat/OutputFormat integration, which enables use of JDG as a highly scalable, high performance data source for Hadoop. This enables use of tools from the Hadoop ecosystem which support InputFormat/OutputFormat for processing on data stored in JDG.
  • Remote Task Execution
    JDG 7 features the ability to execute tasks (business logic) on JDG Server from the Java Hot Rod client. The task can be expressed as a Java executable loaded on JDG Server or as stored JavaScript procedure which executes on the Java 8 (Nashorn) scripting engine on JDG Server.

Continue reading “Announcing Red Hat JBoss Data Grid 7”


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