migrating-to-db

Migrating Logseq graphs from Markdown to database format involves backing up your graph, reviewing its structure, exporting to EDN, configuring import settings, executing the migration steps, and validating data integrity post-migration. Follow the pre-migration checklist to handle namespace decisions, tag-to-class conversions, and property type inference correctly.

Before migration, complete a pre-migration checklist covering your current graph structure, storage setup, tags, properties, and queries. Identify how tags will convert to classes, determine namespace handling, and back up your data. This preparation prevents compatibility and data-integrity issues during conversion.

During MD-to-DB migration, properties undergo type inference to map to database fields, and tags convert to classes based on your decisions. The migration process applies these transformations while maintaining data relationships and ensuring the resulting database structure meets compatibility and performance requirements.

Post-migration validation confirms data integrity and compatibility in your converted database format. Review the migrated graph structure, verify property types and class assignments, check query functionality, and validate sync behavior to ensure the migration completed successfully.

Common migration issues include property type mismatches, namespace conflicts, and incomplete tag-to-class conversions. Recovery strategies involve reviewing pre-migration decisions, re-exporting with corrected settings, and re-importing with adjusted configuration options to resolve data-integrity problems.

Yes, MD-to-DB migration applies across Logseq versions, including version-specific export and import configurations. The migration process handles compatibility differences, ensuring your graph structure, properties, and queries work correctly in the target Logseq version's database format.