How do you manage and search through TBs of B-roll?
Past about a terabyte, the constraint stops being organisation and becomes bandwidth: uploading 4TB over a 50 Mbps connection takes roughly 7.4 days of continuous transfer, so any workflow that starts with "upload your library" is already out. What works is an index that lives next to the footage and stays searchable when the drive is not attached.
Published September 10, 2026 · Field notes
The version of this question posted in r/videoediting is precise about the constraint: about 4TB of raw footage and B-roll on external drives, no usable naming convention, and "uploading terabytes of raw footage is not an option for me (bandwidth and privacy)". That sentence eliminates most of the market before any feature comparison starts, so it is worth doing the arithmetic properly.
The upload maths, done once
4TB is 32 trillion bits. A 50 Mbps upstream link moves 50 million bits per second. That is 640,000 seconds, or 7.4 days of saturated upload with nothing else using the connection. Double the link to 100 Mbps and it is still 3.7 days. Add that most residential and small-studio connections are asymmetric, and that you would be re-uploading every new shoot forever, and the model stops making sense regardless of the subscription price.
This is why the tools that do work at this scale either index locally or index proxies. It is worth checking which of those a given product means when it says local - the distinction, and how to verify it, is in does searching my footage upload it anywhere.
What actually changes past a terabyte
Three things, none of them about organisation:
- The library outgrows one drive. Once footage lives on four drives and two of them are on a shelf, "where is it" becomes a separate question from "what is it". You need a catalogue that outlives the mount point.
- Indexing becomes a background job, not a step. Anything that requires you to wait is abandoned. It has to run while you do something else and pick up where it left off.
- Reads dominate. On a spinning archive drive over USB, the bottleneck for any indexing pass is sequential read of the media, not the model. A pass over multiple terabytes is measured in hours whatever the tool.
What a local index costs in disk
Less than people expect, and the number is calculable rather than mysterious. A semantic index stores one vector per sampled frame. A vector is a fixed-length array of 32-bit floats, so its size is dimensions times four bytes:
- 512-dimension model: 2,048 bytes per frame
- 768-dimension model: 3,072 bytes per frame
In Reelary the sampling cap is 16 frames per video, so at 768 dimensions one video costs at most about 48KB of vectors, and 10,000 videos come to roughly 480MB. Thumbnails and the scrub strips are the larger half of the cache in practice. The point of the arithmetic is not the exact figure - it is that the index is three or four orders of magnitude smaller than the footage, which is what makes it reasonable to keep on your fast internal drive while the media stays on the archive.
These are calculations from the index schema (Float32 vectors, 16-frame cap), not measurements of a production library. We have not yet published a measured indexing benchmark; when we do it will be a method-and-machine writeup rather than a single number.
Keeping archives searchable while they are unplugged
This is the capability that matters most at multi-terabyte scale and the one most tools skip. If the catalogue lives on your system drive, then with the archive on a shelf you can still search it, see the matching frames, and learn which drive and which path the clip is on. You plug the drive in only to open or export.
Reelary keeps a single library database across all indexed folders and marks each item as present, offline (its volume is not mounted) or missing (deleted from a mounted volume). Search results still come back for offline items, with the thumbnail from the cache, so an archive drive works like a card catalogue rather than a black box. Files are referenced in place - nothing is copied into a library folder, and nothing is renamed.
A workable shape for a 4TB library
- Consolidate to a known set of drives and deduplicate first. Indexing three overlapping backups just gives you three copies of every result.
- Keep camera originals immutable, one folder per shoot, dated. See organising raw footage.
- Index once, in the background, with the index on the internal drive.
- Use date and camera metadata as your coarse filter, and visual search for the "man walking in the rain" case where you have no other handle.
- Transcribe the material that has speech. It is a different index for a different question.
When not to use Reelary for this.
If the library is shared - several editors, an assistant ingesting, someone needing to check material out - this is a single-user desktop app and you want a real MAM (iconik, axle.ai, CatDV) instead. If your archive lives on a NAS that you need indexed by the NAS itself rather than by a workstation, we do not run on the NAS; the workstation has to be able to mount the share and read through it. And if your material is mostly long-form talking heads rather than B-roll, transcription will serve you better than visual search for the same effort.
Questions people ask about this
How long does it take to upload 4TB of footage to a cloud service?
On a 50 Mbps upload connection, about 7.4 days of continuous transfer: 4 terabytes is 32 trillion bits, divided by 50 million bits per second is 640,000 seconds. On a 100 Mbps connection it is still about 3.7 days. This is arithmetic, not a benchmark, and it is why cloud-first tools are not a realistic option for large local libraries.
How much disk does a local video search index need?
Far less than the footage. A vector is a fixed-length list of 32-bit floats: at 768 dimensions that is 3,072 bytes per indexed frame. With a cap of 16 sampled frames per video, the vectors for one video come to at most about 48KB, so 10,000 videos is roughly 480MB of vectors before thumbnails. That is arithmetic from the index schema, not a measurement of a real library.
Can I search footage on a drive that is not plugged in?
It depends on where the index lives. If the index and thumbnails are stored on your system drive rather than on the media drive, the catalogue stays searchable while the archive drive is disconnected - you can see what you have and where it is, and only need the drive to open or export the clip. If the index sits on the archive drive, unplugging it takes the search with it.