Benchmarks: Performance advantages to store complex object structures

db4o is fast. In the PolePosition open source database benchmark db4o displays significant performance advantages, especially when it comes to storing complex object structures. Several "circuits" represent different use cases. You can download, modify, and run them for yourself.

The Complex circuit, for instance, shows transaction performance (writing, reading, querying and updating a deep object graph that is composed of multiple different classes with an inheritance hierarchy of 5 levels) for different database products and data access methods. As you can plainly see, resolving the object-relational mismatch by using an object-relational mapper like Hibernate costs a lot of performance. db4o overcomes the trade-off between object-orientation and speed: You can now store objects natively and enjoy great performance gains.

Benchmarks always depend on the nature of a tested task. The PolePosition authors deserve credit because they show which database is a good fit for which task. The rule of thumb is: The flatter and simpler the data, the better you perform with direct SQL access to relational databases, e.g. by JDBC. When object structures become more complex, you can not afford to ignore object databases. If performance is of concern, then Hibernate or other object-relational mapper solutions are not a viable choice, because their negative impact on performance is dramatic.

Below are other benchmark "circuits" that demonstrate different use cases:

• Nestedlists - writing, reading, querying and updating a deep graph of lists. Objects are partially reused within the lists
• Inheritancehierarchy - writing, reading, querying and deleting objects of a class hierarchy with a depth of 5 levels
• Flatobject - writing, updating and deleting plain simple flat objects as well as querying for indexed int members and string members