Apps, connectors, and transforms
Understand protocol compatibility, managed ingestion, and payload conversion.
Apps, connectors, and transforms
Apps, connectors, and transforms connect external data to RawTree in different ways. They complement the normal insert and query interfaces. The resulting rows remain available in tables through SQL.
These are RawTree Cloud and RawTree BYOC service features, where enabled. They handle protocols, source connections, and payload preprocessing outside RawTree. The database stores and queries the resulting rows.
| Concept | Main purpose | Example |
|---|---|---|
| App | Enable compatible ingestion or query protocols for a cluster. | OpenTelemetry, Prometheus, or Splunk. |
| Connector | Run a managed process that reads an external source and delivers records. | Read Kafka topics into a table. |
| Transform | Reshape a supported payload into rows during an insert. | Extract individual CloudWatch log events from a delivery envelope. |
Apps enable familiar protocols
An app enables a supported set of endpoints on a cluster. For example, the OpenTelemetry app accepts traces, logs, and metrics through native protocol endpoints. The Prometheus and Splunk apps add their supported ingestion and query interfaces.
An app is a compatibility layer over the database. It does not replace SQL or require a separate database for each signal. Its supported protocol features still have limits, described in the relevant integration guide.
Apps are installed per cluster. Installation enables endpoints, but does not start or resume the cluster. Uninstallation disables those endpoints. App management and cluster readiness are separate concerns.
Connectors manage a source connection
A connector records how to reach an external source, what to read, and where to write the records. A Kafka connector includes broker access, topic selection, consumer configuration, and destination tables.
Saving a connector does not prove that it is delivering data. Its desired configuration, runtime state, source lag, delivered records, and errors describe different parts of its operation. Pausing requests a halt to ingestion without redefining the destination table. Runtime state shows when the service applies the configuration.
The connector service must be available in the environment. Source credentials, network access, and destination permissions still determine whether delivery can proceed. See Connect Kafka.
Transforms change the row shape
A transform is a built-in preprocessor for a supported source format. It can extract several records from one JSON object and copy useful envelope fields onto each row.
For example, an ordinary insert of a CloudWatch delivery object stores the wrapper as one row. The CloudWatch transform emits one row for each log event. That choice changes what a table row represents.
Transforms act before storage. They do not rewrite existing data, schedule queries, or establish a source connection. The service supports named built-in transforms rather than arbitrary custom transform code. They apply to JSON body inserts, not URL imports.
Native OpenTelemetry ingestion uses the corresponding built-in transforms. An explicit transform on a generic table insert does not require installation of the OpenTelemetry app.
Choose the right combination
A sender that already speaks a supported protocol can use an app. A managed external feed can use a connector. A supported delivery envelope can use a transform. These are choices about transport and row shape, not replacements for access control.
Their success signals also differ. An HTTP request, a connector's saved state, and an accepted export do not prove the same outcome. In particular, OpenTelemetry can report partial success with rejected records. See the Ingestion model.
SQL workflows operate after data is available. They run saved queries and can deliver results to sinks.