Data Integration

Change data capture with Debezium: A simple how-to, Part 1

Change data capture with Debezium: A simple how-to, Part 1

One question always comes up as organizations moving towards being cloud-native, twelve-factor, and stateless: How do you get an organization’s data to these new applications? There are many different patterns out there, but one pattern we will look at today is change data capture. This post is a simple how-to on how to build out a change data capture solution using Debezium within an OpenShift environment. Future posts will also add to this and add additional capabilities.

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First steps with the data virtualization Operator for Red Hat OpenShift

First steps with the data virtualization Operator for Red Hat OpenShift

The Red Hat Integration Q4 release adds many new features and capabilities with an increasing focus around cloud-native data integration. The features I’m most excited about are the introduction of the schema registry, the advancement of change data capture capabilities based on Debezium to technical preview, and data virtualization (technical preview) capabilities.

Data integration is a topic that has not received much attention from the cloud-native community so far, and we will cover it in more detail in future posts. Here, we jump straight into demonstrating the latest release of data virtualization (DV) capabilities on Red Hat OpenShift 4. This is a step-by-step visual tutorial describing how to create a simple virtual database using Red Hat Integration’s data virtualization Operator. By the end of the tutorial, you will learn:

  • How to deploy the DV Operator.
  • How to create a virtual database.
  • How to access the virtual database.

The steps throughout this article work on any Openshift 4.x environment with operator support, even on time- and resource-constrained environments such as the Red Hat OpenShift Interactive Learning Portal.

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JBoss Data Virtualization: Integrating with Impala on Cloudera

JBoss Data Virtualization: Integrating with Impala on Cloudera

Cloudera Impala is a tool to rapidly query Hadoop data in HBase or HDFS using SQL syntax.  You can use Red Hat JBoss Data Virtualization to query that same data via Impala to take advantage of its optimization. You can also combine that data with other data sources in real time.  The goal of this guide is to import data from a Cloudera Impala instance, manipulate it, and then expose that data as a data service.  This guide includes access to a repository with example scripts, creating a custom base and view model, exposing it as a data service, and finally consuming that data via REST. This is a peer article to Unlock Your Cloudera Data with Red Hat JBoss Data Virtualization.

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JBoss Data Virtualization on OpenShift: Integrating a Remote SQL Server Database

JBoss Data Virtualization on OpenShift: Integrating a Remote SQL Server Database

This example shows how on OpenShift to use a custom database driver to connect to an external database, through a Virtual Database (aka VDB). For this example, we will use a Microsoft SQL Server database (believe it or not, running on a Linux container), and the latest SQL Server JDBC driver.

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