Compare Apache Karaf and GlusterFS 
- Users report that GlusterFS excels in scalability, allowing for seamless expansion of storage capacity without significant downtime, while Apache Karaf is noted for its modular architecture, which enables users to easily add or remove features as needed.
- Reviewers mention that GlusterFS has a steeper learning curve, particularly in its setup process, which received a lower score of 7.8 compared to Apache Karaf's 8.9, indicating that users find Karaf easier to configure initially.
- G2 users highlight that GlusterFS's support quality is rated at 7.6, with some users expressing concerns about response times, whereas Apache Karaf's support is slightly lower at 7.4, but users appreciate the community-driven resources available for troubleshooting.
- Users on G2 report that GlusterFS has a strong performance in handling large volumes of data, which is crucial for small businesses, while Apache Karaf is praised for its lightweight nature and quick deployment, making it ideal for rapid application development.
- Reviewers say that GlusterFS's product direction score of 4.4 indicates some uncertainty about future updates, while Apache Karaf's score of 7.3 suggests a more positive outlook on ongoing development and feature enhancements.
- Users mention that GlusterFS is particularly beneficial for organizations needing high availability and redundancy, while Apache Karaf shines in environments where flexibility and integration with existing Java applications are paramount.
Quick setup and running - in a SpringBoot application just add annotation @KafkaListener to your Consumer and you are good to go. Also you can explore more complex setups while using a running application. Also horizontal scalability is a big like.
It felt quite complicated . The solutioning had quite long process of sending a request from database to the outbound application
Easy to setup, works on cheap hardware.
The auto-heal isn't reliable and the process to manually intervene is painful, not exact, and does not scale. Performance suffers when the volumes aren't at 100% health. If underlying I/O isn't consistent the volume can wobble. Community support isn't all...
Quick setup and running - in a SpringBoot application just add annotation @KafkaListener to your Consumer and you are good to go. Also you can explore more complex setups while using a running application. Also horizontal scalability is a big like.
Easy to setup, works on cheap hardware.
It felt quite complicated . The solutioning had quite long process of sending a request from database to the outbound application
The auto-heal isn't reliable and the process to manually intervene is painful, not exact, and does not scale. Performance suffers when the volumes aren't at 100% health. If underlying I/O isn't consistent the volume can wobble. Community support isn't all...
