WebSocket
A bounded batch window over a stream, not real-time delivery.
Read this first
A WebSocket run collects one bounded window of messages and loads it. It is a batch snapshot of a stream. If you need sub-second delivery, Ingest is the wrong tool and this page is telling you so deliberately.
Window bounds
A window ends at whichever comes first: until_idle_seconds, max_messages, max_seconds, or the run
deadline. Always bound the window: an unbounded one is a run that never finishes.
Messages and errors
Each message yields records at message_path, after message_filter. A message matching
error_message_path is an error. Ping/pong keeps the connection alive; a transport drop reconnects
with bounded backoff and resubscribes.
Duplicates
Reconnects can replay. Duplicates are resolved by sequence_field when the protocol has one, and
otherwise by primary key at merge time, never by hoping.
Credential proof
Connect, then read the first message.
Questions
- Which WebSocket sources has Ingest certified?
- None yet. Ingest authors a WebSocket connector from the vendor's own API documentation when a customer asks for it.
- Can Ingest sync any WebSocket API?
- Ingest authors the connector from the vendor's published API documentation, runs it against the real API, and lists it as deployable only once it passes. A connector is a declarative spec, never per-source code, which is why a new one is authored rather than programmed.
- Where can WebSocket data land?
- Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL and Snowflake. The data lands in a destination you own, under credentials you control. Ingest keeps no copy of it.
WebSocket sources, and where they land
The other source kinds Ingest reads: File, GraphQL, gRPC, REST, SOAP, SQL.
Where the tables land: Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL, Snowflake.