This issue is unique.
Your idea.
For a sovereign and independent office suite, true data sovereignty means ensuring users are never locked out of their historical data. Legacy Microsoft Access (.mdb) databases hold decades of critical public, enterprise, and personal records. Relying on proprietary or Windows-exclusive software to open them poses a severe risk to long-term data accessibility. By natively supporting .mdb file reading, Euro-Office guarantees that users can independently recover and migrate their historical data at any time.
Furthermore, once the unified database-to-spreadsheet conversion pipeline is built to support .mdb recovery, it is a natural and low-overhead extension to include support for modern embedded databases like SQLite, as well as analytics-heavy formats like DuckDB and Parquet. It's very common that data analysts and researchers need to quickly inspect datasets using spreadsheet applications, so this bridges the gap between legacy data recovery and modern data science.
All the work has already been done and contributed in PR #45 and related modules/repos.
This issue is unique.
Your idea.
For a sovereign and independent office suite, true data sovereignty means ensuring users are never locked out of their historical data. Legacy Microsoft Access (
.mdb) databases hold decades of critical public, enterprise, and personal records. Relying on proprietary or Windows-exclusive software to open them poses a severe risk to long-term data accessibility. By natively supporting.mdbfile reading, Euro-Office guarantees that users can independently recover and migrate their historical data at any time.Furthermore, once the unified database-to-spreadsheet conversion pipeline is built to support
.mdbrecovery, it is a natural and low-overhead extension to include support for modern embedded databases like SQLite, as well as analytics-heavy formats like DuckDB and Parquet. It's very common that data analysts and researchers need to quickly inspect datasets using spreadsheet applications, so this bridges the gap between legacy data recovery and modern data science.All the work has already been done and contributed in PR #45 and related modules/repos.