NoSQL to SQL migration
done right

Schema Discovery

NoSQLSync samples your source database and infers a complete schema. Detects fields, types, nested structures, and relationships across all collections or tables.

Type Mapping

Every NoSQL type (ObjectId, ISODate, NumberInt, Array, nested Object) is mapped to the best SQL equivalent for your target. You can override any mapping in the visual editor.

Bulk Migration

The initial load transfers all historical data. Parallel workers maximize throughput. You choose the batch size, concurrency, and whether to pause the source application.

Live CDC Sync

Once the bulk load reaches a steady state, CDC takes over. All new writes flow from NoSQL source to SQL target in real time with sub-second latency.

Progress & record counts

Every migration reports records migrated against records total, per collection, so you can confirm the target has caught up with the source before you cut over.

Cutover

When you're confident the data is consistent, switch your application reads and writes to the SQL target. CDC runs until you stop it and NoSQLSync never writes to your source — so pointing the connection string back is your rollback.

Yes — your application keeps writing to the NoSQL source the entire time. NoSQLSync bulk loads the historical data, then CDC replays every new write to the SQL target within a second. The source stays authoritative until you decide to switch your application's connection string to the target, so there is no maintenance window.

Embedded documents become JSONB (PostgreSQL), JSON (MySQL), STRUCT/VARIANT (BigQuery/Snowflake), or normalized join tables. Our schema mapper lets you choose per field. Arrays can become native SQL arrays, JSON arrays, or separate tables.

NoSQLSync samples documents and infers a schema that covers the union of all observed fields. Fields that appear in some documents but not others become nullable columns. You can configure sampling depth and field inference thresholds.

Yes. Apply filter queries to select specific documents or table rows. Filter by date range, status field, or any query your source database supports. Partial migrations are fully supported for both bulk load and CDC.

All data is encrypted in transit (TLS 1.3) and at rest (AES-256). Database credentials use short-lived tokens. Migration workers run in an isolated environment and never store your data after the job completes.

Our schema mapper supports custom type overrides, column renaming, field exclusion, and custom SQL transformations. You can write SQL expressions to transform data during migration (e.g., format dates, concat fields, compute derived columns).