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NanoMD at a glance
NanoMD
NanoMD represents the recurring tendency in documentation tooling to carve out restricted markdown subsets whenever implementers value deterministic parsing, low overhead, and minimal feature surfaces over full compatibility.
ARI at a glance
ARI
Digital photography fragmented into many manufacturer-specific raw formats because camera makers optimized for their own sensors, metadata, and software ecosystems rather than for one shared public raw standard.
Format comparison
| Feature | NanoMD | ARI |
|---|---|---|
| File type | Document | Image |
| Extensions |
|
|
| MIME type |
|
|
| Compression / quality | depends | raw |
| File size characteristics | medium | large |
| Compatibility | broad | limited |
| Editability | moderate | high |
| Created year | 2020 | 2010 |
| Inventor | Community (Markdown variant) | ARRI (Arnold & Richter) |
| Status | active | proprietary |
| Primary use cases |
|
|
| Common software |
|
|
| Archival suitability | strong | strong |
| Metadata handling | moderate | rich |
| Delivery profile | strong | limited |
| Workflow fit | exchange | source |
| Vector scaling | Not supported | Not supported |
When to use each format
When to use NanoMD
- authoring
- review and collaboration
- distribution
- Keeps parsing and rendering requirements intentionally small.
When to use ARI
- capture ingest
- editing
- web or print delivery
- Preserve capture-stage image data for later interpretation.
FAQs
Why convert NanoMD to ARI?
Choose ARI as target when maintaining compatibility with ARRI-originated raw image workflows or preserving frame data for grading and finishing.
What changes when converting NanoMD to ARI?
Convert to ARI when maintaining compatibility with ARRI-originated raw image workflows or preserving frame data for grading and finishing. It is appropriate for professional capture archives and controlled post-production pipelines.
What should I review after converting NanoMD to ARI?
After conversion, review these destination checks: Open converted output in LibRaw and verify behavior on real samples; Compare output against the expected raw quality profile; Many are vendor-specific and poorly documented publicly.
How can I keep quality stable in NanoMD to ARI conversion?
Run representative samples, keep settings deterministic, and monitor these risks: Compatibility often depends on decoder support in tools such as LibRaw, Adobe Camera Raw, or vendor software; Many are vendor-specific and poorly documented publicly; Validate destination compatibility before large-batch conversion.