Engine version details

When you create a StreamSets environment, you select the engine type and version to use. Use the latest engine version so that you have the latest updates and features.

Engine versions are organized by engine type:

Data Collector engine versions

You can use the following Data Collector engine versions.

Data Collector 7.7.x engine details

The Data Collector 7.7.0 engine release occurred on July 29, 2026.

7.7.x new features and enhancements

New Snowflake Streams source: The new Snowflake Streams source reads change capture data from Snowflake Streams. The source reads data from an existing standard table stream.
Snowflake Streaming target renamed: The Snowflake Streaming target is now known as the Snowpipe Streaming target.
Salesforce Lookup processor enhancement: You can use the new Retrieve by custom field lookup mode to perform a lookup by using any field that is defined in your Salesforce objects, instead of using the Id field.; With this mode, the processor groups lookup requests into batches of up to 2,000 records for each Salesforce API call to reduce the number of API calls made to Salesforce. You cannot access deleted records with this new lookup mode.
Salesforce connection support: You can use the Salesforce.com connection in all Salesforce stages and the Tableau CRM target.

7.7.x upgrade impact

Review invalid list entries in required fields: With this release, list entries in required fields are validated, which did not occur in earlier releases.; When you upgrade a flow to 7.7.0, list entries in required fields that use the default value are removed and the remaining list entries are validated.; After upgrade to 7.7.0, review and update flows with invalid list entries in required fields, as needed.; If upgrading to 7.7.0 results in a high number of invalid flows, you can temporarily revert the validation behavior by setting the new validation.listbean.required.enabled Data Collector property to false and restarting the engine.
After you update the invalid flows, set the validation.listbean.required.enabled property back to true or remove the property. false.
Review default data types for Databricks flows: With this release, when a Databricks target receives a record with missing or invalid data in a field type that is not specified in the Data defaults for missing or invalid fields property, the target replaces the missing or invalid data with null values. In previous releases, missing or invalid field values were replaced with the constant /N, which represents an empty value in Databricks.; After you upgrade to 7.7.0, update the Data defaults for missing or invalid fields property as needed to achieve the behavior that you want.

7.7.0 fixed issues

The Snowpipe Streaming target, previously known as the Snowflake Streaming target, only connected to Snowflake with legacy Snowflake account information. With this fix, newer Snowflake account details also work correctly.
The Snowpipe Streaming target, previously known as the Snowflake Streaming target, failed to connect to private URLs.
The Snowflake Bulk source failed with a permissions error when reading from a read-only database, even when a separate staging database was specified.
Data Collector did not connect to a Hashicorp Vault credential store when a namespace was not defined.
Required fields that contain lists were not properly validated. This fix has upgrade impact.

7.7.x known issue

The Oracle CDC source can generate a null pointer exception when the Ignore Materialized Views property is disabled.

Data Collector 7.6.x engine details

The Data Collector 7.6.1 engine release occurred on July 10, 2026.

7.6.x new features and enhancements

Oracle XStream source enhancements

The Oracle XStream source supports downstream capture from pluggable databases. Primary key metadata is not yet included in records.
You can enable the Use Debezium Format property to generate records that use the Debezium format instead of the Data Collector record format.

HTTP Server origin enhancement

For increased security, the origin now performs a strict Server Name Indication (SNI) validation. This update has upgrade impact.

Cloudera CDP support

The Cloudera CDP stage library now supports CDP 7.3.2, updated from 7.3.1. Existing pipelines automatically use the updated stage library. This change has no upgrade impact.

7.6.x upgrade impact

Verify hostname matching for HTTP Server flows

With this release, the HTTP Server origin performs strict Server Name Indication (SNI) validation. When you send data to the HTTP endpoint where the HTTP Server origin listens, the hostname must now match the common name that is specified in the SSL/TLS certificate. Previously, this was not the case.

After you upgrade to 7.6.1, verify if systems send data to the HTTP endpoint with a hostname that matches the common name in the SSL/TLS certificate. Update the hostname as needed.

7.6.1 fixed issue

The Snowflake Bulk source fails to read from read-only databases.

7.6.x known issue

The Oracle CDC origin can generate a null pointer exception when the Ignore Materialized Views property is disabled.

Data Collector 7.5.x engine details

The Data Collector 7.5.0 engine release occurred on May 27, 2026.

7.5.x new features and enhancements

Connections

Oracle connection update - You can now use the Oracle connection in the Oracle XStream source.
New Snowpipe connection - You can use the new Snowpipe connection in the Snowflake target.

Confluent Schema Registry enhancements for Kafka stages

OAuth support - You can now use OAuth authentication to connect to Confluent Schema Registry.
Support for all data formats - You can use the Confluent Schema Registry with JSON and Protobuf data, in addition to the previous Avro support. Before you use Confluent Schema Registry with JSON or Protobuf data, register schemas with Confluent Schema Registry and use the appropriate topic name strategy.
Top-level unions for Avro schemas - You can now use top-level union schemas when you use Confluent Schema Registry with the Kafka Multitopic Consumer source. This enhancement includes support for nullable records, multiple event types within a single schema, and the correct handling of null values.

Apache Iceberg for AWS target enhancement

You can use the new Schema Evolution property to define how the Apache Iceberg for AWS target handles schema changes in incoming data. The target can now add new columns or make compatible changes such as compatible type promotions.

Azure Synapse SQL target enhancement

New staging area authentication:
- You can now use Managed Identity and SAS Token authentication to connect to an Azure Blob Storage staging area, in addition to OAuth and Shared Key authentication.
- You can now use Managed Identity authentication to connect to an ADLS Gen2 staging area, in addition to OAuth and Shared Key authentication.
Property changes - Properties are renamed, replaced, or moved for ease-of-use. For example:
- Staging Authentication is now Authentication Method.
- Data Time Zone is now Data Storage Time Zone.
- Account Name is now Account FQDN, and you should now specify a fully qualified domain name for new pipelines. Existing pipelines are upgraded appropriately.
- Container Name is now Storage Container/File system, and you can specify a file system name in addition to a storage container name.
- Data default properties, such as Numeric Default and Bit Default, are replaced with a Data Defaults for Missing or Invalid Fields property. With the new property, you can specify a default for each selected data type.
Property removals - The following properties are removed:
- Azure Government Account - You can specify a government account in the new Account FQDN property.
- Specify Copy Statement Authentication - With this change, you no longer need to configure Copy statement authentication. The target uses the same authentication that is configured for the stage.
- Directory Template - With this change, you can use only a stage file prefix to name staged files. This update has upgrade impact.

Elasticsearch proxy support

You can now configure Elasticsearch stages and to connect through a proxy.

FTP/SFTP/FTPS Client origin enhancement

You can enable the new Reprocess Files with Same Name property to process consecutive files with the same name when they have different last-modified timestamps.

New Data Collector configuration property

The new avro.iceberg.timestamp.compatibility.enable Data Collector property defines the precision that Data Collector uses when it writes Avro and Parquet data.

You can use this property to enable the Apache Iceberg for AWS target to process timestamp data as expected by Apache Iceberg.

7.5.x upgrade impact

Review Azure Synapse SQL target flows: With this release, the Azure Synapse SQL target no longer includes a Directory Template property for specifying a template for the names of staged files.; After you upgrade to 7.5.0, the target appends sdc as a prefix for the names of staged files. When needed, you can update the Stage File Prefix property to change the prefix.

7.5.0 fixed issues

The IBM watsonx.data target can fail to write data when record fields are in a different order than the target table columns.

7.5.x known issue

The Oracle CDC source can generate a null pointer exception when the Ignore Materialized Views property is disabled.

Data Collector 7.4.x engine details

The Data Collector 7.4.0 engine release occurred on April 30, 2026.

7.4.x new features and enhancements

New connections

You can use the following new connections in StreamSets flows:

Pulsar
Rabbit MQ

Kafka support for IAM access control for Amazon MSK

To access Kafka on Amazon MSK from Kafka stages, you can configure a custom authentication option to use IAM access control.

Data default enhancements for several destinations

The Databricks, Google BigQuery, Snowflake, and Teradata targets now provide a single Data defaults for missing or invalid fields property on the Data Defaults tab.

Use this property to specify default values when a field is missing or contains invalid data. If you do not define a default value, the target writes missing or invalid fields as null. You can specify a different default value for each data type.

Previously, these targets provided a separate default property for each data type. This change has upgrade impact when you use a Snowflake target with the JSON or Parquet staging file format.

Additional Snowflake target enhancements

You can enable a new Allow column number mismatch property to avoid parsing errors that can occur when you enable both data drift processing and multithreaded processing.
You can now use the target to process list data in Variant fields.

7.4.x upgrade impact

Update Snowflake targets that use the JSON or Parquet staging file format

With this release, when you use the JSON or Parquet staging file format and do not define values for the Data defaults for missing or invalid fields property, the Snowflake target writes missing or invalid fields as null.

Previously when you used the JSON or Parquet staging file format and did not define default values, the target wrote missing or invalid fields as \N. To keep the same behavior after you upgrade to 7.4.x, update the Data defaults for missing or invalid fields property to specify \N as the default value for each data type.

Review pipelines that process PostgreSQL interval data

With this release, the format for PostgreSQL Interval fields has changed.

Earlier Data Collector releases used an earlier PostgreSQL driver that included all time units in interval data, even when those units are set to 0. This release includes a PostgreSQL driver update, and the updated driver no longer includes time units that are set to 0 in interval data.

The following table illustrates the difference in processed interval data:

Interval	Interval data 7.3.x and earlier	Interval data with 7.4.0 and later
2 years	`2 years 0 mons 0 days 0 hours 0 mins 0.0 secs`	`2 years`
3 months and 15 days	`0 years 3 mons 15 days 0 hours 0 mins 0.0 secs`	`3 mons 15 days`
2 hours and 30 seconds	`0 years 0 mons 0 days 2 hours 0 mins 30.0 secs`	`2 hours 30 secs`

After you upgrade to Data Collector 7.4.0, review flows that process PostgreSQL interval data and update downstream processing as needed.

The following sources can be used to process PostgreSQL data:

Aurora PostgreSQL CDC Client
JDBC Multitable Consumer
JDBC Query Consumer
PostgreSQL CDC Client

7.4.0 fixed issues

When not using continuous mining, the Oracle CDC Client source performs slowly when configured to use the Direct Fetch strategy.
Snowflake parsing errors can occur in a multithreaded Snowflake target with data drift enabled.
When the Snowflake target runs out of space for the temporary files required for processing, it treats all subsequent data as error records. With this fix, the target generates an error and stops the flow instead.
The JDBC Producer target generates error records when processing data that includes timezone fields.
The Named Pipe target writes the last record of a batch and the first record of the subsequent batch to the same line.
The Azure Data Lake Gen 2 source does not update the offset correctly when used with a path pattern that includes a combination of regular expressions between the file name and wildcards.
Flows that include the Snowflake target are not upgraded properly between Data Collector versions 5.11.0 and 7.3.0. With this fix, you can upgrade Snowflake target flows from earlier versions to Data Collector 7.4.0 without errors.

7.4.x known issue

The Oracle CDC source can generate a null pointer exception when the Ignore Materialized Views property is disabled.

Data Collector 7.3.x engine details

The Data Collector 7.3.0 engine release occurred on March 31, 2026.

7.3.x new features and enhancements

New stages

Oracle XStream source - Use the source to process Oracle change data from redo logs using Oracle XStream.
Apache Iceberg for AWS target - Use the target to write data to Apache Iceberg tables stored on Amazon S3.

Support changes

This release includes the following new support:

Pulsar 4.x in addition to Pulsar 3.x.
Kafka on Confluent Cloud and Confluent Platform 7.3 and later, in addition to Apache Kafka 3.x and 4.x.

Due to the Oracle end of support for Oracle 11g release 2, support for Oracle 11g release 2 has been removed with this release. This update has upgrade impact.

Additional enhancements

New Kafka authentication method - In Kafka stages, you can use the new Confluent Cloud authentication option to connect to Kafka on Confluent Cloud and Confluent Platform.
Elasticsearch connections - Elasticsearch connections include support for an API key authentication mode.
FTP connections - You can now use FTP connections in StreamSets flows. For more information, see Connections.

Deprecated versions

Data Collector engine versions 6.3.x - 7.1.x are now deprecated. They will be removed from service in an upcoming release.

You can no longer configure new environments for the affected engine versions. However, you can continue using existing engines until they are removed.

For uninterrupted service and for the latest updates and features, upgrade to the latest available engine version before May 19, 2026. For more information, see Upgrading Data Collector engines.

7.3.x upgrade impact

Upgrade from Oracle 11g release 2: Starting with this release, Data Collector no longer supports Oracle 11g release 2. If you use Data Collector to process data from Oracle 11g release 2, upgrade to a supported Oracle version.

7.3.0 fixed issues

When configured to produce events and a schema change occurs, the SQL Server CDC Client source can generate duplicate schema-change events after a flow restart.
The SQL Parser processor sometimes stops a flow with an exception.
Several common vulnerabilities have been fixed.

7.3.x known issue

The Oracle CDC source can generate a null pointer exception when the Ignore Materialized Views property is disabled.

Data Collector 7.2.x engine details

The Data Collector 7.2.0 engine release occurred on February 27, 2026.

7.2.x new features and enhancements

IBM Cloud Storage origin enhancement

You can now use the IBM Cloud Storage source to process Parquet data.

Kafka enhancements

Kafka 4.x support - You can now use Kafka stages to process data in Kafka 4.x, in addition to Kafka 3.x. This enhancement has upgrade impact.
Support for SASL/OAUTHBEARER authentication - You can now use SASL/OAUTHBEARER authentication with Kafka stages by choosing the Custom authentication security option and defining related properties.

Web Client response length enhancement

You can now define a maximum entity length in characters and bytes for Web Client stages that log responses.

Improved signing key validation

Signing key sizes for the following stages are now validated according to RFC 7518 specifications:

Salesforce stages
HTTP stages
Web Client stages

7.2.x upgrade impact

Update Web Client stages that use OAuth 2 with signed access tokens: With this release, Web Client stages that use OAuth 2 with signed JWT access tokens now require Base64-encoded signing keys. In earlier releases, signing keys could be provided in plain text and did not require Base64 encoding.; After you upgrade to 7.2.x, ensure that all Web Client stages that use the OAuth 2 authentication method with a signed access token are updated to use a Base64-encoded signing key in the Signing Key property.
Create Kafka topics for Kafka Producer flows: With this release, the topics specified in the Topic property of a Kafka Producer target must exist before the flow starts. If those topics do not exist, the flow fails to start. Before this release, the target created the topics when necessary.; After you upgrade to 7.2.x, ensure that every topic specified in the Topic property of the Kafka Producer target exists in the Kafka cluster before you start the pipeline.; If you use an expression to specify the topics to write to, the Kafka Producer target creates topics as needed. Creating topics in advance is not necessary.

7.2.x known issues

The Oracle CDC source can generate a null pointer exception when the Ignore Materialized Views property is disabled.
When configured to produce events and a schema change occurs, the SQL Server CDC Client source can generate duplicate schema-change events after a flow restart.

Jetstream engine versions

You can use the following Jetstream engine versions.

Jetstream 1.0.0 release notes

The Jetstream 1.0.0 engine release occurred on July 2, 2026.

1.0.x new features and enhancements

New Jetstream engine: Jetstream is a modern engine that is based on core Data Collector features and is optimized to run on Flink.; Unlike Data Collector, the Jetstream engine does not process Jetstream flows. Instead, the engine passes Jetstream flows to Flink for processing.; The Jetstream engine includes Jetstream-only stages and features, such as using multiple origins within a flow. Because Jetstream flows run on Flink, the flows can perform window-based transformations, such as joins and aggregates, on windows of time.; At this time, you can use a limited set of stages in Jetstream flows.; Use Jetstream engines if your environment includes Flink on Confluent Platform.