Unlock Your Cloudera Data with Red Hat JBoss Data Virtualization

After Unlock your Hadoop data with Hortonworks and Red Hat JBoss Data Virtualization episode, let’s continue the journey with another “Apache Hadoop” episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogeneous data sources.

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External materialized views demystified in Red Hat JBoss Data Virtualization and Red Hat JBoss Data Grid

Red Hat JBoss Data Virtualization (JDV) provides several capabilities for caching data including: materialized views, result set caching, and code table caching. These techniques can be used to significantly improve performance in many situations.

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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.

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Unlock your Microsoft Excel data with Red Hat JBoss Data Virtualization

After Unlock your MariaDB/MySQL data, Unlock your PostgreSQL data, and Unlock your Hadoop data with Hortonworks episodes, let’s continue the journey with this new episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogeneous data sources.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. It 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. By providing the following functionality, JDV enables agile data use:

  1. Connect: Access data from multiple, heterogeneous data sources.
  2. Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
  3. Consume: Makes unified data easily consumable through open standards interfaces.

It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with.

This post will guide you step-by-step on how to connect JDV to a Microsoft Excel spreadsheet using Teiid Designer and the Microsoft Excel translator. A translator acts as the bridge between JBoss Data Virtualization and an external system. The Microsoft Excel translator provides a quick and easy way to read a Microsoft Excel spreadsheet and provides contents of the spreadsheet in the tabular form that can be integrated with other sources.

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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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Unlock your PostgreSQL data with Red Hat JBoss Data Virtualization

And here we go for another episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogeneous data sources.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. It 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. By providing the following functionality, JDV enables agile data use:

  1. Connect: Access data from multiple, heterogeneous data sources.
  2. Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
  3. Consume: Makes unified data easily consumable through open standards interfaces.

It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with. This post will guide you step-by-step on how to connect JDV to a PostgreSQL database using Teiid Designer. We will connect to a PostgreSQL database using the PostgreSQL JDBC driver.

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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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