Java developers who need to store and retrieve persistent data already have several options available to them: serialization, JDBC, object-relational mapping tools, object databases, and entity EJBs. Why introduce yet another persistence framework? The answer to this question is that each of the aforementioned persistence solutions has severe limitations. JDO attempts to overcome these limitations, as illustrated by the table below.
Table 2.1. Persistence Mechanisms
Supports: | Serialization | JDBC | O-R Tool | Object DB | EJB | JDO |
---|---|---|---|---|---|---|
Java Objects | Yes | No | Yes | Yes | Yes | Yes |
Advanced OO Concepts | Yes | No | Yes | Yes | No | Yes |
Transactional Integrity | No | Yes | Yes | Yes | Yes | Yes |
Concurrency | No | Yes | Yes | Yes | Yes | Yes |
Large Data Sets | No | Yes | Yes | Yes | Yes | Yes |
Existing Schema | No | Yes | Yes | No | Yes | Yes |
Queries | No | Yes | Yes | Yes | Yes | Yes |
Strict Standards / Portability | Yes | No | No | No | Yes | Yes |
Simplicity | Yes | Yes | Yes | Yes | No | Yes |
Serialization is Java's built-in mechanism for transforming an object graph into a series of bytes, which can then be sent over the network or stored in a file. Serialization is very easy to use, but it is also very limited. It must store and retrieve the entire object graph at once, making it unsuitable for dealing with large amounts of data. It cannot undo changes that are made to objects if an error occurs while updating information, making it unsuitable for applications that require strict data integrity. Multiple threads or programs cannot read and write the same serialized data concurrently without conflicting with each other. It provides no query capabilities. All these factors make serialization useless for all but the most trivial persistence needs.
Many developers use the Java Database Connectivity (JDBC) APIs to manipulate persistent data in relational databases. JDBC overcomes most of the shortcomings of serialization: it can handle large amounts of data, has mechanisms to ensure data integrity, supports concurrent access to information, and has a sophisticated query language in SQL. Unfortunately, JDBC does not duplicate serialization's ease of use. The relational paradigm used by JDBC was not designed for storing objects, and therefore forces you to either abandon object-oriented programming for the portions of your code that deal with persistent data, or to find a way of mapping object-oriented concepts like inheritance to relational databases yourself.
Several software companies created frameworks to perform the mapping between objects and relational database tables for you. These object-relational mapping products allow you to focus on the object model and not concern yourself with the mismatch between the object-oriented and relational paradigms. Unfortunately, each object-relational mapping product has its own set of APIs. Your code becomes tied to the proprietary interfaces of a single vendor. If the vendor raises prices or fails to fix show-stopping bugs, you cannot switch to another product without rewriting all of your persistence code. This is referred to as vendor lock-in.
Rather than map objects to relational databases, some software companies developed a new form of database designed specifically to store objects. These object databases are often much easier to use than object-relational mapping software. The Object Database Management Group (ODMG) was formed to create a standard API for accessing object databases; few object database vendors, however, comply with the ODMG's recommendations. Thus, vendor lock-in plagues object databases as well. Many companies are also hesitant to switch from tried-and-true relational systems to the relatively new object database technology. Fewer data-analysis tools are available for object database systems, and there are vast quantities of data already stored in older relational databases. For all of these reasons and more, object databases have not caught on as well as their creators hoped.
The Enterprise Edition of the Java platform introduced entity Enterprise Java Beans (EJBs). Entity EJBs are components that represent persistent information in a data store. Like object-relational mapping solutions, entity EJBs provide an object-oriented view of persistent data. Unlike object-relational software, however, entity EJBs are not limited to relational databases; the persistent information they represent may come from an Enterprise Information System (EIS) or other storage device. Also, EJBs use a strict standard, making them portable across vendors. Unfortunately, the EJB standard is somewhat limited in the object-oriented concepts it can represent. Advanced features like inheritance, polymorphism, and complex relations are absent. Additionally, EJBs are difficult to code, and they require heavyweight and often expensive application servers to run. EJBs, especially session and message-driven beans, do have other advantages, however, and so the JDO specification details how JDO can integrate with them.
JDO combines many of the best features from each of the persistence mechanisms listed above. Creating persistent classes under JDO is as simple as creating serializable classes. JDO supports the large data sets, data consistency, concurrent use, and query capabilities of JDBC. Like object-relational software and object databases, it allows the use of advanced object-oriented concepts such as inheritance. It avoids vendor lock-in by relying on a strict specification like entity EJBs. Also like entity EJBs, JDO does not prescribe any specific back-end data store. JDO implementations might store objects in relational databases, object databases, flat files, or any other persistent storage device.
![]() | Note |
---|---|
By default, Kodo JDO stores objects in relational databases using JDBC. It can be customized for use with other data stores. |
JDO is not ideal for every application. For many applications, though, it provides an exciting alternative to other persistence mechanisms.