Download JAR files tagged by criteria with all dependencies

This project basically aims to create an abstraction layer above common ORM used this days and provide a simplified DAO layer which is not only independent of the ORM tool being used but also integrated with other services, for example App Layer Caching, Free Text Search Engine etc. Initial target is to implement it for Hibernate and when JPA provides Hibernate's Criteria like API implement for JPA as well. Integrate App Layer Cache and Compass Framework.

This Jackrabbit subproject is an object/JCR persistence and query service. This tools lets you to persist java objects into a JCR compliant repository - including association, inheritance, polymorphism, composition, and the Java collections framework. Furthermore, this jcr-mapping allows you to express queries in Java-based Criteria, as well as in JCR query language. It offers also features like version support and object locking.

Burningwave core is an advanced, free and open source Java library that contains THE MOST POWERFUL CLASSPATH SCANNER for criteria based classes search. It’s possible to search classes by every criteria that your immagination can made by using lambda expressions. Burningwave core scan engine is highly optimized using direct allocated ByteBuffers to avoid heap saturation; searches are executed in multithreading context and are not affected by “the issue of the same class loaded by different classloaders” (normally if you try to execute "isAssignableFrom" method on a same class loaded from different classloader it return false). This library is useful also for creating classes during runtime, facilitate the use of reflection and much more...

A bank decides using various criteria whether a customer wil receive a loan. An insurer uses specific information to determine which insurance product is most suitable for its customer. A municipality makes decisions based on yet other information, to determine whether it will grant permits or if a citizen is entitled to a public transport pass. Decision trees are frequently used in order to make such decisions or recommendations. Albero is a new generation decision tree solution. It is simple, fast, and flexible. Further, Albero is easily adaptable and can integrate easily into any environment.

A bank decides using various criteria whether a customer wil receive a loan. An insurer uses specific information to determine which insurance product is most suitable for its customer. A municipality makes decisions based on yet other information, to determine whether it will grant permits or if a citizen is entitled to a public transport pass. Decision trees are frequently used in order to make such decisions or recommendations. Albero is a new generation decision tree solution. It is simple, fast, and flexible. Further, Albero is easily adaptable and can integrate easily into any environment.

A bank decides using various criteria whether a customer wil receive a loan. An insurer uses specific information to determine which insurance product is most suitable for its customer. A municipality makes decisions based on yet other information, to determine whether it will grant permits or if a citizen is entitled to a public transport pass. Decision trees are frequently used in order to make such decisions or recommendations. Albero is a new generation decision tree solution. It is simple, fast, and flexible. Further, Albero is easily adaptable and can integrate easily into any environment.

A bank decides using various criteria whether a customer wil receive a loan. An insurer uses specific information to determine which insurance product is most suitable for its customer. A municipality makes decisions based on yet other information, to determine whether it will grant permits or if a citizen is entitled to a public transport pass. Decision trees are frequently used in order to make such decisions or recommendations. Albero is a new generation decision tree solution. It is simple, fast, and flexible. Further, Albero is easily adaptable and can integrate easily into any environment.

A bank decides using various criteria whether a customer wil receive a loan. An insurer uses specific information to determine which insurance product is most suitable for its customer. A municipality makes decisions based on yet other information, to determine whether it will grant permits or if a citizen is entitled to a public transport pass. Decision trees are frequently used in order to make such decisions or recommendations. Albero is a new generation decision tree solution. It is simple, fast, and flexible. Further, Albero is easily adaptable and can integrate easily into any environment.