About
AutoDAO is a Generic DAO on steroids implementation for Java.
This project was inspired by Don't repeat the DAO! article by Per Mellqvist.
Main features
* Ready to use CRUD operations
* Zero persistence code for common DAO queries
* Annotation-driven auto-configuration
* Spring Framework custom namespace for easy to use configuration
* Hibernate/JPA support
The goal of Autofetch is reduce the modularity penalty and programmer burden of specifying associations which should be loaded with an object query. These specifications are sometimes are called fetch profiles, prefetch directives, or joins. These specifications are an important performance optimization because they reduce the number of round-trips to a persistence store whether that be a relational database, object database, or flat file. Autofetch is a library which integrates with object persistence tools and automatically handles prefetching data. Using dynamic program profiling, Autofetch determines the right prefetch directives for each query a program executes.
What is Ebean?
Ebean is a Object Relational Mapping Persistence Layer written in Java (Open Source LGPL license).
* Providing the features of EJB3's JPA (and more)
* No container required
* JPA compatible ORM mapping (@Entity, @OneToMany, ...)
Why use Ebean?
Ebean provides a simpler approach to Object Relational Mapping. It does this by not requiring session objects such as JPA EntityManager, JDO PersistenceManager, Hibernate Session, Toplink ClientSession.
With the addition of generics in Java 5, writing a custom DAO for each domain object is no longer required. There are a wide variety of articles on creating generic DAOs, but my current project uses the approach from this IBM DeveloperWorks article. This approach was choses mainly because of the clearly written article and the integration with Spring. You should be able to extend any generic DAO based on Spring to implement the stored procedure configuration.
The DataNucleus project provides products for the management of application data in a Java environment. Our aim is to provide good quality open source products to handle data in all of its forms, wherever it is stored. This goes from persistence of data into heterogeneous datastores, to providing methods of retrieval using a range of query languages, and eventually on to the analysis of data and tools for managing data quality. Your use of DataNucleus products will mean that you don't need to take significant time in learning the oddities of particular datastores, or query languages and instead use a single common interface for all of your data, and instead your team can concentrate their application development time on adding business logic and let DataNucleus take care of data management issues.