XML Databinding frameworks

When I began looking at the available data binding frameworks I was surprised to see that they didn't perform all that well compared with document models such as dom4j. This was contrary to my expectations, since the data binding approach actually reduces the amount of document information kept in memory -- a document model holds on to everything, while a data binding only needs the actual data. I thought that an approach that works with less data should generally be faster than one that works with more.

The aspect I questioned was the use of a SAX2 parser for unmarshalling documents. SAX2 is a very useful standard for parsing XML, but its event driven approach is not well suited to data binding and similar applications. The problem here is that the code processing the SAX2 events needs to maintain state information for everything it processes, and this adds both complexity and overhead.

I created the code that grew into JiBX to test some ways around these problematic aspects of the other data binding frameworks, and to experiment with extending the mapped binding approach beyond what's supported by Castor. Instead of reflection, JiBX uses byte code enhancement to add hooks into application code at project build time. Instead of SAX2, JiBX is based on a pull parser architecture (currently XMLPull). Rather than generating code from a DTD or Schema, JiBX works with a binding definition that associates user-supplied classes with XML structure.

These techniques are not unique to JiBX. Byte code enhancement is used by many JDO (Java Data Objects) implementations for basically the same purpose as in JiBX (to add access hooks to existing compiled code). The original JAXB code (since discarded) was based on a pull parser architecture similar to XMLPull. The mapped approach to data binding is supported (although with some limitations) by both Castor and Quick. Even though the individual techniques aren't new, the combination of them still makes for a very interesting alternative to the other data binding frameworks.

JiBX's use of a pull parser also helps keep the runtime small and efficient, as does its limited validation support - JiBX automatically checks many aspects of a document based on your mapping when unmarshalling, but does not support in-memory validation.