JORAM

JORAM is a JMS compliant enterprise messaging middleware.

JORAM (Java Open Reliable Asynchronous Messaging) is an open source implementation of the Java Message Service (JMS) API (1.1, 2.0 and 3.0).
It implements proprietary, AMQP, MQTT, Stomp and Rest connector and integrates many inter-broker bridge (JMS, AMQP, Rest/JMS, etc.).

Status

Mature

License(s)

GNU Lesser General Public License v2.1 only

Website

https://joram.ow2.io/

Documentation

http://joram.ow2.org/doc/tutorials.html

VCS repository(ies)

- type: git
web: https://gitlab.ow2.org/joram/

Issue tracker URL

https://gitlab.ow2.org/joram/joram/issues

Discussion channels

http://mail.ow2.org/wws/lists/projects/joram

Project leader(s)

Andre Freyssinet

News

Professional support

http://www.scalagent.com/

Standards

AMQP JDBC JMS JNDI JTA Java EE MQTT OSGi REST SOAP WebSocket

Market Readiness Synthesis

Launched in 1999, JORAM is a standard-compliant, well proven, simple-to-use and mature open source implementation of the Java Message Service (JMS) specification. Professional support is provided by the maintainer team at French SME ScalAgent D.T. Evolutions such as add-ons and performance improvements are usually user-sponsored and regularly contributed to the core product. JORAM is well suited to implement asynchronous mechanisms that reduce bottlenecks in SaaS/Cloud architectures. JORAM is an alternative to Oracle Weblogic, IBM MQseries and Apache ActiveMQ.

Market Readiness Level

Project Market Readiness Level computed by OW2.

More on the definition and computation of Market Readiness Levels here.

Best Practices Implementation

Coverage of best practices in open source software development implemented by the project.

More on best practices and how they are collected here.

Project Profile

Computation of the project's profile through five key attributes defined by OW2.

More on how project attributes are commputed here.

MRL Assessment Diagram

This page lists the control points used in our assessment of the project's market readiness with their normalised values. It shows how they are combined to form the model. Please go to the methodology overview for more on the model and data collection.