Versant Knowledge Base

The Versant Knowledge Base is a compilation of resources bringing together comprehensive information about database technology, white papers, detailed product resources and more. Here you'll find the resources to get into object-oriented data management and become productive using our products.

Versant Database Engine Information

Versant provides a variety of technical resources to help you understand object-oriented data management and to support you to become productive using the Versant Database Engine.

The Basics

Learn the basics of our object persistence technology and how it compares to traditional database technologies.

Product Information
  • Product Overview Versant Object Database Versant Database Engine 8.0 is designed to handle the navigational access, seamless data distribution, and enterprise scale often required by applications that use complex C++ and Java object models, have high concurrency requirements, and large data sets.
Online Screencasts
  • Screencasts: First Steps Versant Object Database In these 15-minutes practice oriented screencasts we demonstrate how easy it is to transparently and efficiently persist your data with Versant Database Engine – from an OO modell to data persistence in no time. Screencasts are available either for Java (JVI) and C++.
Compatibility Overview
Datasheets
Whitepapers
  • An ever growing number of whitepapers explore various aspects of Versant Database Engine. Topics include application applicability, optimizing your hardware platform, scalability issues and more. We want you to get the most out of VDE. Click here for the full list.
Documentation
What is an Object Oriented Database?
  • An OODBMS combines object oriented programming principles with database management principles Object oriented programming concepts such as encapsulation, polymorphism and inheritance are enforced as well as database management concepts such as the ACID properties which lead to system integrity, support ad hoc query languages and secondary storage management systems which allow for managing big data.
    A primary feature of an OODBMS is that accessing objects in the database is done in a transparent manner such that interaction with persistent objects is no different from interacting with in-memory objects.
    Because the database is integrated with the programming language, the programmer can maintain consistency within one environment (both the OODBMS and the programming language will use the same model of representation) while using the same development tools. And because there's no fundamental mismatch between the programming and database models no costly data mapping is required which translates into unprecedented performance gains when dealing with persistence in a complex object domain.
  • Learn more about Object Databases by visiting ODBMS.ORG ODBMS.ORG is designed to meet the fast-growing need for resources focusing on object database technology, objects and databases, the integration of object-oriented programming and databases, persistent object life cycle management, object oriented persistence technologies, cloud data stores and NoSQL databases.
    Don't miss their Introduction to Object Database Management Systems.
  • ODBMSs and Relational Databases Most applications use a relational database as their data store while using an object oriented programming language for development. This causes a certain inefficiency as objects must be mapped to tuples in the database and viceversa instead of the data being stored in a way that is consistent with the programming model. The "impedance mismatch" caused by having to map objects to tables and viceversa has long been accepted as a necessary performance penalty. Why not getting rid of this complex mapping process by using a database that follows the same model as your application? Enter the Object Database!
  • Use the Magic Cube to select your database technology Magic Cube is a simple, visual tool created by Versant to help you compare database technologies. It looks at the principle application requirements along the three axis that impact the overall system performance: data volume, data complexity and concurrency. Each axis in the Magic Cube represents one criteria: Concurrency, Data/Model Complexity, Data Volume.