HOFA CD-Burn.DDP.Master vs Matchering
HOFA CD-Burn.DDP.Master
hofa-plugins.deMatchering
github.comSide by side
| Figure | HOFA CD-Burn.DDP.Master | Matchering |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Audio Mastering Software | 8.2 (#6) | 8.7 (#1) |
Plans
In their own words
HOFA CD-Burn.DDP.Master
HOFA CD-Burn.DDP.Master is a standalone mastering and pre-mastering application for CD, DDP, vinyl, and online distribution projects. It burns Red Book audio CDs and creates DDP images carrying CD-Text, ISRC, and EAN information. Editing includes cutting, trimming, fades, crossfades, and track metadata. Album sequencing, multi-CD projects, multi-session CDs, and batch processing are supported. Delivery options include DDP images, WAV, AIFF, MP3, and an iTunes itmsp package. HOFA plugins are included at no additional cost in the app, with automatable parameters, and the software connects to HOFA DDP Player Maker for client-review players. The standard edition does not list third-party VST3 or AU plugins, plugin-chain presets, clip-based plugin processing, or true-peak normalization; those are listed for PRO. It runs on macOS 10.13 or later and Windows 10 or later. The listed plan costs 89.90 EUR once, with a 14-day free trial and offline activation.
Matchering
Matchering is open-source software for matching and mastering audio. Give it a TARGET track and a REFERENCE track, and it produces a mastered TARGET that follows the reference’s RMS, frequency response, peak amplitude, and stereo width. Matchering 2.0 comes as a containerized web application, Python library, and ComfyUI node, and is integrated into the UVR5 Desktop App. The Python library also provides a command-line application and can connect with the Python ecosystem. It requires Python 3.8.0 or later and a machine with 4 GB of RAM. WAV and MP3 are supported input formats, though MP3 loading needs a separate FFmpeg installation. The project says the algorithm uses digital signal processing rather than a neural network, and works well across nearly all genres, especially EDM, with an exception for experimental music with a very specific form. The free plan is listed at free under GPLv3, with no published paid plans. The maker advises against exposing its web application to the public Internet without security and scalability changes.