Data Virtualization Primer

Introduction

 

  1. Introduction

  2. The Concepts (SOAs, Data Services, Connectors, Models, VDBs)

  3. Architecture

  4. On Premise Server Installation

  5. JBDS and Integration Stack Installation

  6. WebUI Installation

  7. Teiid Designer - Using simple CSV/XML Datasources (Teiid Project, Perspective, Federation, VDB)

  8. JBoss Management Console

  9. The WebUI

  10. The Dashboard Builder

 

11. OData with VDB

12. JDBC Client

13. ODBC Client

14. DV on Openshift

15. DV on Containers (Docker)

Series 1 the basics

series 2 and 3

Data Virtualization Primer Series 2 The Connectors (Planned)

Data Virtualization Primer Series 3 Solutions (Planned)

a. Big Data Example

b. IoT Example

c. Cloud Example

d. Mobile Example

e. JBoss Multi-product examples (Fuse/BPMS/BRMS/Feedhenry/DG)

What is it?

JBoss Data Virtualization offers comprehensive data abstraction, federation, integration, transformation, and delivery capabilities to combine data from one or multiple sources into reusable and unified logical data models accessible thru standard SQL (JDBC, ODBC, Hibernate) and/or web services (REST, OData, SOAP) interfaces for agile data utilization and sharing.

  • Connect: Access data from multiple, heterogeneous data sources.

  • Compose: Easily create reusable, business-friendly logical data models and views by combining and transforming data.

  • Consume: Make unified data easily consumable through open standard interfaces.

Data Virtualization Includes

  • Tools for creating data views that are accessible through standard protocols (the Teiid Designer plug-in for Red Hat JBoss Developer Studio (JBDS)).

  • A robust runtime environment that provides enterprise-class performance, data integrity, and security (the Red Hat JBoss Data Virtualization Server, which executes as a process within the Red Hat JBoss Enterprise Application Platform (EAP)).

  • A repository for storing metadata (ModeShape)

  • A WebUI (Developer Preview) to create your Data Services and manage your Data Library

Community projects

Data virtualization components

Use Cases

  • Strategic Initiative
  • Business Intelligence
  • 360 Degree View
  • SOA Data Services
  • Security
  • Big Data
  • Cloud Data

Deliver strategic technology initiatives with agility

Red Hat JBoss Data Virtualization lets users get the actionable, unified information they want, the way they want it, and at the speed their business needs it. Combined with ease of development, JBoss Data Virtualization allows rapid delivery for a range of IT projects and initiatives.

Agile, self-service business intelligence (BI)

If your organization struggles with uncontrollable point-to-point integration, you’ll benefit from JBoss Data Virtualization. By unifying data access for analytics, JBoss Data Virtualization:

  • Simplifies data access.
  • Improves reuse.
  • Reduces change impact.
  • Achieves consistent semantics.

Unified, 360° view

Applications often need an aggregated view of data from master data management (MDM), data warehouse (DW), and other online transaction processing (OLTP) systems to gain a complete view of data in real time.

Agile Soa Data Services

Data virtualization delivers the data services to SOA apps. It speeds the creation of data services that encapsulate the data access logic, and lets multiple business services acquire data from a centralized data layer.

Data Firewall

Data virtualization provides reverse proxy access to data, keeping physical data sources anonymous. This prevents unnecessary exposure.

Get improved data quality via centralized access control, robust security infrastructure, and a reduction in physical copies of data to reduce risk.

A metadata repository catalogs enterprise data locations, and the relationships between the data in various data stores provide transparency and visibility.

Big Data integration

More and more organizations have big data stored in Hadoop and NoSQL systems. But most reporting and analytical tools can't access those database servers, because most require an SQL interface. Data virtualization provides the solution by masking these sources as SQL tables.

Cloud data integration

Many organizations are adopting cloud computing that requires each new cloud source to be integrated with the existing IT environment. Data virtualization solves this problem, allowing enterprises to maintain a complete view of internal and external information while taking advantage of attractive cloud economics.

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