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* Enhancements o New plugins provide enhanced capabilities: + Hibernate Plugin: # allows to generate SQL statements from Hibernate HQL statements # shows object tree of mapped objec

SchemaCrawler is an open-source Java API that makes working with database metadata as easy as working with plain old Java objects. SchemaCrawler is also a command-line tool to output your database schema and data in a readable form. The output is designed to be diff-ed with previous versions of your database schema.

With AutoPatch, an agile development process that requires a database change looks like this: Developer alters the model, which requires a change to the database Developer possibly consults a DBA, and develops a SQL patch against their personal database that implements the alteration Developer commits the patch to source control at the same time as they commit their dependent code Other developers' and environments' databases are automatically updated by AutoPatch the next time the new source is run This represents streamlined environment maintenance, allowing developers to cheaply have their own databases and all databases to stay in synch with massively lower costs and no environment skew. That's what AutoPatch does. Clusters with one database? Multiple schemas? Logical migrations, instead of just DDL changes? Need to do something special/custom? Need to distribute your changes commercially? All without paying anything? No problem.

Database Change Management You never develop code without version control, why do you develop your database without it? Liquibase is an open source (Apache 2.0 Licensed), database-independent library for tracking, managing and applying database changes. It is built on a simple premise: All database changes are stored in a human readable yet trackable form and checked into source control. Liquibase Supports: Extensibility Merging changes from multiple developers Code branches Multiple Databases Managing production data as well as various test datasets Cluster-safe database upgrades Automated updates or generation of SQL scripts that can be approved and applied by a DBA Update rollbacks Database "diff"s Generating starting change logs from existing database

migrate4j is a database migration tool. Suppose you determine that you need a new database table for your project. If you develop alone, you could write an SQL script that adds a table and manually apply this to your development system. But if you work with other developers, or need to keep a test system in synch with your development system, this become tedious and error prone. Migration tools make it possible to add your new table (or make any other schema changes) in an automated fashion, ensuring all your systems are always in synch. Migration tools also make it possible to quickly and easily roll back previous changes. Unlike typing commands into an interactive SQL window or storing SQL scripts, migration tools keep a detailed history of how your database schema evolved (just in case you need to go back to a previous version). Finally, migration tools minimize or eliminate the problem of having to use vendor specific syntax - you may never switch database products, but if you do, using a migration tool will make your life much easier. The initial intent of migrate4j was to make a Java version of Ruby's db:migrate. If you've used db:migrate, you probably fell in love with it's simple syntax, easy configuration and ability to roll changes up and back effortlessly. The intent (and the challenge) of migrate4j is to bring the power and simplicity of db:migrate to Java programmers, using familiar type safety and syntax. Along the way, we're adding additional functionality that makes migrate4j more than just another Ruby tool rewritten for Java - it is a Java project intended to make other Java projects even better.

Querydsl is a framework which enables the construction of type-safe SQL-like queries for multiple backends including JPA, JDO and SQL in Java. Instead of writing queries as inline strings or externalizing them into XML files they are constructed via a fluent API. Code completion in IDE (all properties, methods and operations can be expanded in your favorite Java IDE) Almost no syntactically invalid queries allowed (type-safe on all levels) Domain types and properties can be referenced safely (no Strings involved!) Adopts better to refactoring changes in domain types Incremental query definition is easier Querydsl is licensed under the LGPL 2.1 license.

As we have just released the first milestone of the Spring Data JPA project I'd like to give you a quick introduction into its features. As you probably know, the Spring framework provides support to build a JPA based data access layer. So what does Spring Data JPA add to this base support? To answer that question I'd like to start with the data access components for a sample domain implemented using plain JPA + Spring and point out areas that leave room for improvement. After we've done that I will refactor the implementations to use the Spring Data JPA features to address these problem areas. The sample project as well as a step by step guide of the refactoring steps can be found on Github.