SQL Flow writes one source stream to a durable spool, then advances relational replicas and event sinks on independent cursors.
The job to be done
A capability matters when it removes an operational decision, not when it adds another checkbox. SQL Flow connects source-aware capture, durable progress, target apply, and validation so the page you are reading leads to a usable operating path.
Database targets use convergent apply while Kafka and Pub/Sub receive serialized events. Each sink owns its checkpoint, batching, and error policy. SQL Flow handles independent cursor and lag per sink; pause or add a sink without restarting capture; table-aware Kafka topic routing; stable event deduplication identifiers.
Why this path matters
Database targets use convergent apply while Kafka and Pub/Sub receive serialized events. Each sink owns its checkpoint, batching, and error policy. SQL Flow handles independent cursor and lag per sink; pause or add a sink without restarting capture; table-aware Kafka topic routing; stable event deduplication identifiers.
What changes for you
Destination-specific workers preserve the shared source order while choosing the apply contract appropriate to each target. SQL Flow handles target-specific batching and connection reuse; JSON and Protobuf event serialization; retry, skip, fail, and dead-letter policies; source-only monitoring when no sink is needed.
The outcome
List the replicas, topics, subscriptions, and SLAs. We will map them into independent delivery contracts.
The payoff
Add destinations without adding source readers.
Keep fresh, queryable copies for apps and reporting.
Publish table-aware change events.
Where the work happens
Read each capability as part of the operating path. The important question is not whether a feature exists, but what work it removes and what evidence it leaves behind.
One durable stream
Database targets use convergent apply while Kafka and Pub/Sub receive serialized events. Each sink owns its checkpoint, batching, and error policy.
SQL Flow handles independent cursor and lag per sink; pause or add a sink without restarting capture; table-aware Kafka topic routing; stable event deduplication identifiers.
Mixed consumers
Destination-specific workers preserve the shared source order while choosing the apply contract appropriate to each target.
SQL Flow handles target-specific batching and connection reuse; JSON and Protobuf event serialization; retry, skip, fail, and dead-letter policies; source-only monitoring when no sink is needed.
Before you choose
Use the page-specific details below as a short discovery checklist. They are the conditions and work areas that shape the capability, not generic product promises.
The path to confidence
The page keeps the product detail close to the decision it supports. Your team can see what the software handles automatically, what it changes for the target, and what the result leaves ready to operate.
Database targets use convergent apply while Kafka and Pub/Sub receive serialized events. Each sink owns its checkpoint, batching, and error policy. SQL Flow handles independent cursor and lag per sink; pause or add a sink without restarting capture; table-aware Kafka topic routing; stable event deduplication identifiers.
Destination-specific workers preserve the shared source order while choosing the apply contract appropriate to each target. SQL Flow handles target-specific batching and connection reuse; JSON and Protobuf event serialization; retry, skip, fail, and dead-letter policies; source-only monitoring when no sink is needed.
Keep the plan connected
A capability becomes easier to operate when the next decision follows from the constraint you just uncovered. Explore the related work that completes this part of the path.
Your working set
Take the next step
List the replicas, topics, subscriptions, and SLAs. We will map them into independent delivery contracts.
Talk through my use case