Almost every developer knows the problem to read large sets of data from the database. It may crash your application with an OutOfMemoryError and cripple its performance.

As a consequence, filtering and processing large results may even further increase memory consumption.

Luckily, there is a convenient remedy using Hibernate and Kotlin sequences.

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Hibernate internally uses an abstract metadata model to validate the data model defined by the declared entities. The framework also offers entry points to enhance this metadata model with custom code.

In this article we show how to extend the generated metadata model using annotations. Our example is to implement a convenient way to define common table prefixes for subclasses of a “@MappedSuperclass” entity.

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For optimal performance developers often define database indexes in the JPA data model classes. While this is relatively easy at entity class level, it becomes quite cumbersome if you your model consists of a deeply nested inheritance hierarchy using “mapped” super classes. I.e., there is no direct way that indexes defined for super classes will be added to entities automatically. Instead you have to repeat them every time.

In this article we show how to to circumvent this problem using Hibernate’s MetadataBuilderImplementor SPI.

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Docker is a great tool for developing micro services that may be composed together in order to form a larger application. However, Docker containers run in a network apart from the host machine. That makes it sometimes cumbersome and complicated to use common host names within the Docker network and the host network. In this article we’ll show a simple knack that may be applied in order to use identical host names in both networks.

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Apache Camel is a powerful routing and conversion engine use in many projects. In this article we present some best practices when integrating Camel into the JBoss application server aka WildFly/EAP7. Most of this is straight-forward, yet we also faced some problems with the thread pool management.

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We’re glad to announce the new release of the GuttenBase database migration framework. The main but not only goal of this framework is to support database migrations between different (heterogenous) RDBMS, such as DB2, MySQL or Oracle. During the copying process you may apply various transformations such as data mapping, columns alteration, renaming tables, …

The 2.0 release features among various API enhancements and speed improvements: Java 8 support, a new tool to copy schemas between different databases, more supported database types, mapping of proprietary database column types, new documentation, …

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When developing applications using the JBoss EAP/WildFly application server there is a repetitive task that has been solved differently over and over again: The configuration of the application server, i.e. installing JDBC drivers, startup scripts, data sources, JMS destinations, logging categories, etc.
Within our company there are several projects addressing this problem. In this post we’d like to propose a project to combine all those different requirements and experiences into a single build system.

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In march we are publishing our new Technology Radar as you know from last years. You can participate as usual – just follow the link:

http://goo.gl/fnw5yf

You can participate until friday, february 20th 2015. We are looking forward to your ratings for the trends in 2015 and technologies to build on for web based business applications.

Additional information for the last radars: http://radar.akquinet.de/

Thanks for participating

akquinet AG