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prepare 5.0.0 changelog

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CHANGELOG.md
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# Changelog
## [5.0.0]
CommaFeed is now powered by Quarkus instead of Dropwizard. Read the rationale behind this change in
the [announcement](https://github.com/Athou/commafeed/discussions/1517).
The gist of it is that CommaFeed can now be compiled to a native binary, resulting in blazing fast startup times (around
0.3s) and very low memory footprint (< 50M).
- CommaFeed now has a different package for each supported database.
- If you are deploying CommaFeed with a precompiled package, please
read [this section of the README](https://github.com/Athou/commafeed/tree/master?tab=readme-ov-file#download-a-precompiled-package).
- If you are building CommaFeed from sources, please
read [this section of the README](https://github.com/Athou/commafeed/tree/master?tab=readme-ov-file#build-from-sources).
- If you are using the Docker image, please read the instructions on
the [Docker Hub page](https://hub.docker.com/r/athou/commafeed).
- Due to the switch to Quarkus, the way CommaFeed is configured is very different (the `config.yml` file is gone).
Please
read [this section of the README](https://github.com/Athou/commafeed/tree/master?tab=readme-ov-file#configuration).
Note that some configuration elements have been removed or renamed for consistency.
- Added a setting to prevent parsing large feeds to avoid out of memory errors. The default is 5MB.
- Use a different icon for filtering unread entries and marking an entry as read (#1506)
- Added various HTML attributes to ease custom JS/CSS customization (#1507)
- The Redis cache has been removed. There have been multiple enhancements to the feed refresh engine and it is no longer
needed, even for instances with a large number of feeds.
- The H2 migration tool that automatically upgrades H2 databases from format 2 to 3 has been removed. If you're using
the H2 embedded database, please upgrade to at least version 4.3.0 before upgrading to CommaFeed 5.0.0.
## [4.6.0]
- switched from Temurin to OpenJ9 as the JVM used in the Docker image, resulting in memory usage reduction by up to 50%