Continuous replication and fan-out
One source reader. Every destination advances independently.
Committed changes enter a shared durable spool once. Each sink owns a cursor, apply strategy, error policy, and lag measurement.
Independent fan-outOne committed stream. Every consumer connected.
4 cursors advancing
Durable streamOne ordered history
PostgreSQLIndependent cursor
Azure SQL HyperScaleIndependent cursor
KafkaIndependent cursor
Fabric MirrorOpen Mirroring
Once
Decode the source
Capture cost does not multiply with sinks.
N cursors
Independent progress
Slow sinks do not redefine the others.
Durable
Backlog and catch-up
Unavailable targets recover from spool state.
Independent consumers
Isolation without duplicating capture.
Relational, event-stream, and Fabric destinations read the same ordered source history through destination-specific workers.
✓ One-to-many delivery from one spool
✓ Per-destination checkpoints and lag
✓ Parallel keyed apply where safe
✓ Source-only monitoring mode
Backpressure with a boundary
Choose what happens when retention fills.
Segments, checksums, compression, indexes, and torn-tail recovery make backlog a durable operating state with an explicit retention policy.
✓ Configurable retention and limits
✓ Backlog bytes and drain ETA
✓ Independent cursor garbage collection
✓ Pause and resume with checkpoints
Keep exploring
See the connected parts of the platform.
Map every consumer before adding another reader.
Tell us the source, destinations, latency, and outages. We will size cursors, retention, and apply.