What's new in Replicate November 2025?

This section describes the new and enhanced features in Replicate November 2025.

Customers should also review the Replicate release notes in Qlik Community for information about the following:

• Migration and upgrade
• End of life/support features
• Deprecated versions
• Resolved issues
• Known issues

Migration of legacy Snowflake endpoints to the new unified Snowflake target endpoint

As notified in the previous release, upgrading to Replicate November 2025 will seamlessly migrate any standalone Snowflake target endpoints to the new unified Snowflake target endpoint, using your existing license.

The new Snowflake target endpoint incorporates the functionality of the legacy standalone Snowflake endpoints while adding the following functionality:

• Support for connecting via a proxy server when replicating to Snowflake on Azure
• Support for the Storage Integration Name property when replicating to Snowflake on Azure or Snowflake on AWS
• Support for the use of internal Snowflake staging when replicating to Snowflake on Google.
• Support for connecting via a proxy server to the Snowflake database, to the external storage, or both.

Using Snowflake as a target

Microsoft Fabric endpoint - Open Mirroring support

Fabric Mirroring is a new way for ingesting data into Fabric tables. According to Microsoft, “Mirroring in Fabric is a low-cost and low-latency solution to bring data from various systems together into a single analytics platform.” To facilitate this new functionality, the Microsoft Fabric Data Warehouse endpoint has been renamed to Microsoft Fabric and the option to choose Data Warehouse or Mirrored Database as the Database Type has been added to the endpoint's General tab. When this option is selected, a new OneLake landing zone field will be shown in the Fabric Access (formerly ODBC Access) section. Additionally, the Staging on Azure and Data Loading settings will reflect the selected database type (Data Warehouse or Mirrored Database).

Setting general connection properties

New "Create a metadata file on table creation" option for the Microsoft Azure ADLS endpoint

In previous version, when the Create metadata files in the target folder option was enabled, Replicate would generate a metadata file (DFM) for each data file. The metadata would contain information about the task, the table structure, and the associated data file. Now, customers can also select the new Create a metadata file on table creation option, which creates a metadata file during table creation. The new metadata file contains information about the task and the table structure only. This is useful when running a task in Metadata only mode or when the source table is empty - both of which will result in no data files being transferred to target. By providing details of the table structure, the new metadata file will help customers prepare their downstream applications accordingly. To align with the new option, the existing Create metadata files in the target folder option has been renamed to Create a metadata file for each data file.

Metadata files

Data type enhancements

Snowflake target endpoint

In previous versions, the Replicate WSTRING data type was mapped to Snowflake as follows:

If length is => 21846 and =< 2147483647, then VARCHAR (65535)

From this version, it will be mapped as follows:

If length is => 21846 and =< 2147483647, then VARCHAR (16777216)

Support for the JSON data type

• The JSON data type is now supported by the following endpoints:

  • Teradata target

  • Amazon Redshift target (mapped to SUPER)

    See also: <link to new options in the Advanced tab of the Amazon redshift endpoint>

  • PostgreSQL source
  • Oracle source
  • Oracle XStream source

Support for the XML data type

• The XML data type is now supported by the following endpoints:
  • PostgreSQL target
  • IBM DB2 for z/OS source

Google BigQuery

The following data type changes have been made to Google BigQuery endpoint:

• INT64 instead of INTEGER

• FLOAT64 instead of FLOAT

• BOOL instead of BOOLEAN

Parallel Load support

The Parallel Load feature now supports the following target endpoints:

• Databricks

• SingleStore

IBM DB2 for iSeries endpoint: Multi-member table support

In IBM DB2 for iSeries, a table (physical file) can consist of multiple members, which are similar to SQL table partitions. In previous versions, during Full Load, Replicate would only transfer data from the default (usually first) member. From this version, it will now be possible to replicate data from all table members, using aliases. The data will be loaded from any alias that is associated with a member of the base table. Consequently, customers who want to use this new option need to define aliases for each of the table members before starting the task, as members without an alias will not be included in the Full Load.

To facilitate this new functionality, the following options have been added to the Advanced tab:

• Replicate all members of the table (the default)

• Replicate the first member only

Multi-member tables

DDL History control table: Newly supported endpoints

The attrep_ddl_history (DDL History) control table contains a history of DDL changes that occurred on the source during replication to the target.

The following target endpoints are now supported:

• Google BigQuery
• Google Cloud Alloy DB for PostgreSQL
• Google Cloud SQL for PostgreSQL
• Microsoft Azure Database for PostgreSQL
• PostgreSQL

Enhancement to the “header__change_mask” header column

When using Change Tables with Parquet format, the header column header__change_mask will now pad zeros to the right (instead of to the left) to match the little endian rule.

Affected target endpoints:

• Amazon S3

• Microsoft Azure ADLS

• Google Cloud Storage

Newly supported endpoint and driver versions

Newly supported endpoint versions

The following source and target endpoint versions are now supported:

• MongoDB source: 8.x
• Kafka target: 4.0.x
• SAP Sybase ASE target:16.1

Newly supported driver versions

The following driver versions are now supported:

• SAP Adaptive Server Enterprise ODBC Driver 16.1 (64-bit)

  Information noteRequires RHEL 9 or later and Windows Server 2022 or later
• Microsoft ODBC Driver 18.5
• MySQL 8.4

Newly supported OS versions

This version introduces support for Windows Server 2025.

End-of-life endpoints and driver versions

End-of-life endpoints

The Snowflake on AWS, Snowflake on Google, and Snowflake on Azure endpoints have been superseded by the new Snowflake target endpoint, as mentioned above.

End-of-life endpoint versions

• Databricks 11.3 LTS and 10.4 LTS

• MariaDB 10.5 source and target

• PostgreSQL source and target 13.x

End-of-life driver versions

Microsoft ODBC Driver 18.3

Support for mapping of JSON/XML source data types to their equivalent target data types

The following settings have been added to the Target Metadata tab in the task settings:

• Map compatible source columns to JSON on the target

• Map compatible source columns to XML on the target

When selected (the default), JSON and XML columns will be mapped to the corresponding data types on the target. When not selected or if the target does not support an equivalent data type, the "old" mapping will be used (usually STRING/WSTRING/CLOB/NCLOB according to the target endpoint).

Target metadata