Move the complete dataset with parallel work you can operate.
Burst Load profiles the source, divides large tables into bounded slices, moves many independent units concurrently, and records enough progress to resume unfinished work without repeating completed data.
orders2.4B rows
TargetBulk ingest Use bounded workers across large tables and independent objects.
Start from measured behavior and tune only the exceptions.
Restart unfinished slices without restarting the complete move.
Plan
Turn a database into schedulable work.
Omni Loader inspects tables, keys, sizes, and target behavior before execution. Large tables become concurrent ranges while smaller tables move alongside them, all within explicit worker and bandwidth limits.
Run and recover
Keep useful work when a long move is interrupted.
Progress belongs to durable work units rather than one fragile process. Failed or interrupted slices return to the queue while completed slices remain complete, making restarts proportional to what is left.
Specialized outputs
Use the same engine for rows, objects, and analytical loads.
Extract large binary values to object storage, produce compressed warehouse-ready files, or apply precise transformation and mapping rules without replacing the movement engine.
Keep exploring
See the connected parts of the platform.
See slicing, workers, and throughput boundaries.
See adaptive defaults and measured exceptions.
See durable work-unit recovery.
Move binary values into object storage.
Run versioned plans from automation.
Build parallel analytical loads.
Apply shared rules and table overrides.
Turn the full move into bounded, restartable work.
Bring table sizes, keys, source limits, target ingestion, and the migration window. We will map slices, workers, recovery, and delivery.