Oxygen offers support for importing database data, MS Excel files and text files into XML documents, that can be further converted into other formats using the Transform features. The user can examine the database contents and select the table to be exported using the database browser. It is possible to refine the data source by editing the generated SQL select statement in order to join multiple tables or to use advanced SQL expressions. Oxygen can generate an XML Schema from the database structure.

Analysis At its annual analyst conference last week, IBM announced its next generation database. The big news is that this will not be a relational database. Or, to be more accurate, it will not just be a relational database.

More and more often, enterprise developers of all stripes (Java, VB/.NET, C++, etc.) are asked to build cross-database access for applications and end users. A growing list of methods to exploit features and libraries in JDBC, OBDC, ADOdb, JDO, SQL and XML are available to developers for such one-off integration projects.

A comparison of relational and object model techniques is shown in the following table

This figure presents a comparison of some basic terms used in relational and object technology...

Inheritance in the object model is a means of defining one class in terms of another. This is common usage for most of us. For example, a conifer is a type of tree. There are certain characteristics that are true for all trees, yet there are specific characteristics for conifers.

Encapsulation is the object model concept of including processing or behavior with the object instances defined by the class. Encapsulation allows code and data to be packaged together. The definition of methods for a class is an integral part of encapsulation. A method is programming code that performs the behavior an object instance can exhibit. Calculating the age of a person would be an example of such behavior.

Data abstraction is the process of distilling data down to its essentials. In an object schema, the abstract data model is implemented as a graph. The following figure shows such a graph structure for a genealogical database. For more information on data abstraction, see the items under "more detail" below.

Instance locking locks a single relational tuple in an RDBMS or a single object in an ODBMS. This type of concurrency control is illustrated below.

Class or table locking means that all instances of either a class or table are locked, as is illustrated below. This shows one form of concurrency control. Note the circle at the lower left. It represents all instances of a class, regardless of the page where they are stored.

Cluster locking or container locking for concurrency control is illustrated in the figure below. In this form of locking, all data clustered together (on a page or multiple pages) will be locked simultaneously. This applies only to clusters of objects in ODBMSs. Note that in this example, the cluster of objects spans portions of three pages.

Page locking (or page-level locking) concurrency control is shown in the figure below. In this situation, all the data on a specific page are locked. A page is a common unit of storage in computer systems and is used by all types of DBMSs. In this figure, each rectangle represents a page. Locking for objects is on the left and page locking for relational tuples is on the right. If the concept of pages is new to you, just think of a page as a unit of space on the disk where multiple data instances are stored.

Concurrency control and locking is the mechanism used by DBMSs for the sharing of data. Atomicity, consistency, and isolation are achieved through concurrency control and locking.

Maintaining updates of committed transactions is critical. These updates must never be lost. The ACID property of durability addresses this need. Durability refers to the ability of the system to recover committed transaction updates if either the system or the storage media fails. Features to consider for durability:

The isolation portion of the ACID properties is needed when there are concurrent transactions. Concurrent transactions are transactions that occur at the same time, such as shared multiple users accessing shared objects. This situation is illustrated at the top of the figure as activities occurring over time. The safeguards used by a DBMS to prevent conflicts between concurrent transactions are a concept referred to as isolation.

Consistency is the ACID property that ensures that any changes to values in an instance are consistent with changes to other values in the same instance. A consistency constraint is a predicate on data which server as a precondition, post-condition, and transformation condition on any transaction.

The phrase "all or nothing" succinctly describes the first ACID property of atomicity. When an update occurs to a database, either all or none of the update becomes available to anyone beyond the user or application performing the update. This update to the database is called a transaction and it either commits or aborts. This means that only a fragment of the update cannot be placed into the database, should a problem occur with either the hardware or the software involved. Features to consider for atomicity:

ACID properties are an important concept for databases. The acronym stands for Atomicity, Consistency, Isolation, and Durability.

Object DBMSs allow you to store objects directly without any mapping to different data structures. Relational DBMSs require mapping from objects to tables. This mapping to different data structures is called "impedance mismatch." The figure below shows direct storage at the left and impedance mismatch at the right.

Transparent persistence in object database products refers to the ability to directly manipulate data stored in a database using an object programming language. This is in contrast to a database sub-language used by embedded SQL or a call interface used by ODBC or JDBC. Using an object database product means that you have higher performance and less code to write.