Apache Kafka
Publish table-aware change events for independent downstream consumers.
11 shipped CDC destinations
Capture once. Put each change where work happens.
Apply one durable stream to cataloged relational targets, event consumers, and Microsoft Fabric. Every destination owns its cursor, batching, lag, pause, and recovery state.
One captured streamOrdered change events
PostgreSQLRelational sink
Azure SQL HyperScaleRelational sink
KafkaRelational sink
Fabric MirrorOpen Mirroring
Shared database catalog
Relational CDC destinations
Azure SQL
Catalog details →
CockroachDB
Catalog details →
Google Spanner
Catalog details →
MySQL
Catalog details →
Oracle
Catalog details →
PostgreSQL
Catalog details →
SAP Adaptive Server Enterprise
Catalog details →
SQL Server
Catalog details →
Event and Fabric connectors
Streams and mirrored files
P
Google Cloud Pub/Sub
Deliver JSON change events with identifiers consumers can use for deduplication.
Microsoft Fabric Open Mirroring
Produce and publish the change files expected by Fabric Open Mirroring.
Give every destination its own delivery contract.
Tell us every target, freshness goal, key strategy, and consumer. We will map connector behavior, independent fan-out, and recovery.
SQL Flow handles automatically
The software does the migration work.
- SQL Flow selects a destination-aware loading and apply strategy.
- Compatible schemas, batching, progress, and errors are handled automatically.
- Each destination advances and recovers independently.
You choose
Keep control of the decisions that matter.
- Choose database, event-stream, warehouse, lake, or Fabric destinations.
- Set creation, mapping, performance, and error policy.
- Choose where each destination begins and how it is validated.