Businesses are seeking to benefit from every customer interaction with real-time personalized experience. Targeting each customer with relevant offers can greatly improve customer loyalty, but we must first understand the customer. We have to be able to draw on data and other resources from diverse systems, such as marketing, customer service, fraud, and business operations. With the advent of modern technologies and agile methodologies, we also want to be able to empower citizen integrators (typically business users who understand business and client needs) to create custom software. What we need is one single functional domain where the information is harmonized in a homogeneous way.
Continue reading Event streaming and data federation: A citizen integrator’s story
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.
Continue reading “First steps with the data virtualization Operator for Red Hat OpenShift”
Red Hat is proud to announce the release of JBoss Data Virtualization (JDV) 6.4
JBoss Data Virtualization is a data integration solution that sits in front of multiple data sources and allows them to be treated as a single source, delivering the right data, in the required form, at the right time to any application and/or user.
JDV 6.4 Features
The JBoss Data Virtualization 6.4 release focuses on supporting new and updating existing cloud, big data, and in-memory data sources.
Continue reading “New Release of Red Hat JBoss Data Virtualization.”
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.
Continue reading “JBoss Data Virtualization: Integrating with Impala on Cloudera”
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.
Continue reading “JBoss Data Virtualization on OpenShift: Integrating a Remote SQL Server Database”
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.
Continue reading “Unlock Your Cloudera 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:
- Connect: Access data from multiple, heterogeneous data sources.
- Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
- 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.
Continue reading “Unlock your Microsoft Excel data with Red Hat JBoss Data Virtualization”