---
sourceDocument: Brazil Workflow Data Fabric
sourceDocumentLink: https://www.servicenow.com/docs/r/integrate-applications

 Release :

    - brazil

ft:locale :

    - en-US

ft:publication_title :

    - Brazil Workflow Data Fabric

ft:clusterId :

    - crint

bundleId :

    - crint

workflow :

    - Creator


---

# Configure an Extract Transform Load (ETL) consumer

# Configure an Extract Transform Load (ETL) consumer {#ariaid-title1}

Release version: Brazil  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read  
Import and process data from your Kafka environment using your existing Robust
Transform Engine (RTE) configurations.

## Before you begin

* Role required: integration_hub_admin
* This consumer requires a Stream Connect subscription. For more information, see <https://www.servicenow.com/now-platform/workflow-data-fabric.html>.
* The ServiceNow Stream Connect Installer \[com.glide.hub.stream_connect.installer\] plugin is required.
* This consumer requires a [robust import set
  transformer](https://www.servicenow.com/docs/iqm~R5Lxe1ztOZufzFtwAQ "Use robust import set transformers instead of transform maps if you want to extract, transform, and load data to one or more target tables.").
{#configure-etl-consumer__ul_ity_vdq_hvb}

## About this task

To configure a consumer, you need to create two records.

1. The consumer record, which specifies how to import and process data.
2. A record for the Kafka stream, which defines the stream of data to your consumer.

{#configure-etl-consumer__ol_orv_nx1_mvb}This task covers the consumer creation. For instructions on creating a Kafka stream, see [Create a Kafka stream](https://www.servicenow.com/docs/yhcuYGyyKUpmM_qQz3oEPw "Define a data stream for an Extract Transform Load (ETL), Transform Map, or Script consumer. A Kafka stream defines the stream of data to your consumer.").

## Procedure

1. Navigate to AllIntegrationHubConsumersETL Consumer.
2. Select New.
3. In the form, fill in the fields.  
   {#configure-etl-consumer__table_wvt_wgq_hvb__entry__2}

   | Field | Description |
   |-|-|
   | Name | Name of the ETL consumer. |
   | Robust import set transformer | Name of the robust import set transformer to use to process data. |
   | Delivery guarantee | If there's a node failure, option to specify the delivery guarantee for incoming messages. Select one of the following. * No lost but duplicates: All messages are delivered at least once. Some messages might be delivered more than once. * Once or not at all: A message isn't delivered more than once. Some messages might not be delivered at all. {#configure-etl-consumer__ul_br1_bmq_hvb} |
   | Serialization format | The serialization format for the message. Select one of the following. * Plain Text: Select this option for any plain-text messages. This is the default format. * Encoded: Select this option for messages in an Apache Avro format. Converting plain-text messages to an Avro format requires a schema. Select the schema registry in the Schema registry field. For more information on schemas, see [Schema management in Stream Connect](https://www.servicenow.com/docs/bw99rPqa9MT1fMcg4EjjTg "Import and create schemas to send and receive messages in an Apache Avro format. Using an Avro format can reduce the size of the payload and simplify your integration to your local Kafka instance."). {#configure-etl-consumer__ul_svj_dgf_gbc} |
   | Data in single column | Option to have the import set table store data in single column. |
   | Column mapping | Option to specify whether the message's JSON key maps the data to the column's name or label in the import set table. Select one of the following. * Label * Column name {#configure-etl-consumer__ul_a1b_2mq_hvb}This field appears only when the Data in a single column check box is cleared. |
   | Application | Application scope for the ETL Consumer. |
   | Schema registry | Registry for the selected schema. Select one of the following. * Standalone Schema Registry * Confluent Schema Registry {#configure-etl-consumer__ul_gsw_qff_gbc} This field appears only when the Serialization format is set to Encoded. For the Confluent Schema Registry, if the received message's schema ID isn't in the schema table, the system imports the schema dynamically, using the configured REST connection. |
   [Table 1. Kafka ETL Consumer]

   {#configure-etl-consumer__table_wvt_wgq_hvb}
4. Select Save.

## What to do next

[Create a Kafka stream](https://www.servicenow.com/docs/yhcuYGyyKUpmM_qQz3oEPw "Define a data stream for an Extract Transform Load (ETL), Transform Map, or Script consumer. A Kafka stream defines the stream of data to your consumer.") for this consumer. After the stream is
activated, you can start receiving messages from your Kafka environment.

*[\>]: and then