While acknowledging that Network Attached Storage (NAS) manufacturers or software developers are primarily responsible for this, I've long considered proposing a significant improvement. Open documentation of specifications and related details would enable the creation of tools for NAS scanning that rival the speed of other storage systems. This would be a tremendous advantage, given the vast amounts of data NAS devices typically hold. Efficient indexing of this data, similar to other storage types, would be transformative. Content indexing presents a separate challenge, but hopefully, solutions leveraging Large Language Models (LLMs) are being developed to achieve next-level file management—one that offers speed and efficiency without requiring substantial investment in ultra-fast NVMe SSDs. It might also be necessary to re-envision some of "Everything's" future internal mechanisms, creating separate databases for each storage type and distinct algorithms for indexing hot versus cold storage.
If NAS manufacturers, tech experts, and software developers would simply expose their internal file system protocols and database formats—much like the accessible NTFS/ReFS Master File Tables (MFTs)—then third-party indexing tools could finally attain "Everything"-like speeds. This would allow for direct access and indexing of these internal structures, facilitating lightning-fast retrieval of filenames, paths, and basic file information, thereby circumventing the frustrating inefficiencies of traditional network scanning for colossal datasets.
If NAS manufacturers, tech experts, and software developers would simply expose their internal file system protocols and database formats—much like the accessible NTFS/ReFS Master File Tables (MFTs)—then third-party indexing tools could finally attain "Everything"-like speeds. This would allow for direct access and indexing of these internal structures, facilitating lightning-fast retrieval of filenames, paths, and basic file information, thereby circumventing the frustrating inefficiencies of traditional network scanning for colossal datasets.
Statistics: Posted by eagleeyez — Fri Jul 18, 2025 7:28 pm
