Paul Krill
Editor at Large

ActiveJ Java platform takes aim at Spring, Quarkus

news
Dec 10, 20202 mins

High-performance Java platform born in ad-tech is geared toward high-load web, cloud, networking, and microservices applications

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Positioned as a replacement for multiple Java technologies, the ActiveJ platform is being put forward as a minimalistic, boilerplate-free, and fast technology stack for web, cloud, microservices, and high-load applications.

Consisting of loosely coupled components for asynchronous processing, I/O processing, high-performance web serving, and high-performance networking, ActiveJ, from the company of the same name, was built to replace Spring, Spark, Red Hat Quarkus, Micronaut, Vert.x, and other Java frameworks.

The approach of the ActiveJ platform is to give priority to business logic instead of framework specifications. Open source ActiveJ was created as a high-load ecosystem for the AdKernel real-time ad bidding and ad serving platform, after developers found existing Java platforms and frameworks lacking. ActiveJ 3.0, available since November and accessible on Maven, has been used in in-house projects at AdKernel, processing billions of daily requests.

ActiveJ has few third-party dependencies, the company says, and consists of a set of components that also can be used independently. These components include:

  • ActiveInject is a library for lightweight dependency injection.
  • ActiveSerializer provides space-efficient serializers developed with bytecode engineering. A schema-less approach is used to enhance performance.
  • ActiveCodeGen is a dynamic class and bytecode generator atop the ObjectWeb ASM library. The complexity of direct bytecode manipulation is abstracted and custom classes can be created on the fly.
  • ActiveRPC is a high-performance binary protocol for building distributed applications that require efficient client-server connections between servers.
  • ActiveFS is a lightweight asynchronous library for scalable, remote file storage, supporting data redundancy, resharding, and rebalancing.
  • ActiveSpecializer optimizes code for the JVM code for speed.
Paul Krill

Paul Krill is editor at large at InfoWorld. Paul has been covering computer technology as a news and feature reporter for more than 35 years, including 30 years at InfoWorld. He has specialized in coverage of software development tools and technologies since the 1990s, and he continues to lead InfoWorld’s news coverage of software development platforms including Java and .NET and programming languages including JavaScript, TypeScript, PHP, Python, Ruby, Rust, and Go. Long trusted as a reporter who prioritizes accuracy, integrity, and the best interests of readers, Paul is sought out by technology companies and industry organizations who want to reach InfoWorld’s audience of software developers and other information technology professionals. Paul has won a “Best Technology News Coverage” award from IDG.

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