Kafka Connect Single Message Transform Reference for Confluent Cloud

Single Message Transforms (SMTs) are per-message transformations that modify messages as they flow between connectors and Kafka. They:

• Transform inbound messages after a source connector produces them but before they are written to Kafka.

• Transform outbound messages before they are sent to a sink connector.

Tip

For a tutorial and an in-depth exploration of this topic, see How to Use Single Message Transforms in Kafka Connect.

The following SMTs are available for Confluent Cloud:

Transform	Description
AdjustPrecisionAndScale	Adjust the precision and scale of decimal fields within a record’s key or value.
BytesToString	Convert binary data (bytes field) in a Kafka Connect structure into a string format.
Cast	Cast fields or the entire key or value to a specific type (for example, to force an integer field to a smaller width).
ChangeTopicCase	Change the case of the record topic name (for example, to uppercase or lowercase).
Drop	Drop either a key or a value from a record and set it to null.
DropHeaders	Drop one or more headers from each record.
EventRouter	Only available for Oracle XStream CDC source and managed Debezium connectors. Route Debezium outbox events using a regex configuration option.
ExtractField	Extract the specified field from a Struct when schema present, or a Map in the case of schemaless data. Any null values are passed through unmodified.
ExtractNestedField	Promote a nested field within the record key or value to a top-level field to simplify data access for downstream systems.
ExtractTimestamp	Extract the timestamp from a field within the record key or value and use it to overwrite the record’s existing timestamp.
ExtractTopic	Replace the record topic with a new topic derived from its key or value.
ExtractXPath	Extract specific elements or attributes from XML data and place them into the record’s key or value.
Filter (Apache Kafka)	Drop all records. Designed to be used in conjunction with a Predicate.
Filter (Confluent)	Include or drop records that match a configurable filter.condition.
Flatten (Kafka)	Flatten a nested data structure. This generates names for each field by concatenating the field names at each level with a configurable delimiter character.
Flatten (Confluent)	Flatten a nested data structure including nested maps. This generates names for each field by concatenating the field names at each level with a configurable delimiter character.
FromXML	Convert XML data (stored as bytes or a string) into a strongly typed Connect structure, allowing conversion to formats like Avro.
HeaderFrom	Moves or copies fields in a record key or value into the record’s header.
HeaderToValue	Moves or copies fields in the record header to a record key or value.
HoistField	Wrap data using the specified field name in a Struct when schema present, or a Map in the case of schemaless data.
InsertField	Insert field using attributes from the record metadata or a configured static value.
InsertHeader	Insert a literal value as a record header.
KeyToValue	Convert a record key into a field within the record value (by default, a string field named _key) to store key data directly within the value.
MaskField	Mask specified fields with a valid null value for the field type.
MessageTimeStampRouter	Update the record’s topic field as a function of the original topic value and the record’s timestamp field.
ReplaceField (Apache Kafka)	Filter or rename fields.
ReplaceField (Confluent)	Filter or rename nested fields.
SetMaximumPrecision	Only available for managed source connectors. Ensure all decimal fields in a Kafka Connect structure do not exceed a specified maximum precision.
SetSchemaMetadata	Set the schema name, version, or both on the record’s key or value schema.
TimestampConverter	Convert timestamps between different formats such as Unix epoch, strings, and Connect Date and Timestamp types.
TimestampNow	Replace the existing timestamp of an incoming record with the precise time the record is processed by the connector.
TimestampNowField	Add a new field to the record key or value, populating it with the system timestamp at the moment of processing.
TimestampRouter	Update the record’s topic field as a function of the original topic value and the record timestamp.
TimescaleDB	Only available for Debezium PostgreSQL CDC V2 Source connectors. Process raw change event records captured from TimescaleDB databases, performing logical routing and adding relevant metadata.
TimezoneConverter	Only available for Oracle XStream CDC source and managed Debezium connectors. Convert the timezone of timestamp fields in Debezium change event records to a specified target timezone.
TombstoneHandler	Manage tombstone records. A tombstone record is defined as a record with the entire value field being null, whether or not it has ValueSchema.
TopicRegexRouter	Only available for managed Source and JDBC Sink connectors. Update the record topic using the configured regular expression and replacement string.
ValueToKey	Replace the record key with a new key formed from a subset of fields in the record value.

If the available SMTs don’t meet your transformation requirements, you can create your own SMT for Confluent Cloud. For more information, see Configure Custom SMT for Kafka Connectors in Confluent Cloud.