Enterprise Mainframe Change Data Capture (CDC) to Apache Kafka with tcVISION and Confluent

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software, Inc. and Ram Dhakne, Solutions Engineer at Confluent


This blog focuses on using Treehouse Software’s tcVISION to replicate data in real time between mainframes and Confluent, allowing for new use cases and truly setting data in motion.

Why mainframe modernization? Benefits and use cases

Mainframe data stores often hold large amounts of complex and critical data in proprietary legacy formats, making this data difficult to extract and incompatible with modern databases, data types, and data tools.

Enterprises are looking to take advantage of the latest cloud services, such as analytics, artificial intelligence (AI) and machine learning, scalable storage, security, high availability, etc., or move data to a variety of newer databases. Additionally, many customers want to modernize their application on a cloud or open systems platform without disrupting the existing critical work on the legacy system.

How tcVISION syncs legacy data for the cloud

tcVISION is a data replication software product that performs real-time synchronization of mainframe data sources and cloud and open systems, allowing critical mainframe data to be consumed by a variety of leading cloud services.

tcVISION supports many mainframe data sources for both online and offline scenarios. Data can be replicated from IBM Db2 z/OS, Db2 z/VSE, VSAM, IMS/DB, CA IDMS, CA Datacom, or Software AG ADABAS. tcVISION can replicate data to many targets including Confluent Platform, Apache Kafka®, AWS, Google Cloud, Microsoft Azure, PostgreSQL, Snowflake, etc. To learn more, see the complete list of supported tcVISION sources and targets.


tcVISION focuses on CDC (change data capture) when transferring information between mainframe data sources and cloud and open systems databases and applications. Through innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to a variety of cloud and open systems targets.

tcVISION stores metadata in a relational database and the tcVISION manager components are administered by the tcVISION control board, a Windows GUI interface, which can be installed on premises or in the cloud. This allows tcVISION users to create metadata, create and control replication scripts, and control database interactions. tcVISION’s architecture is designed to minimize mainframe resource utilization.

Using the tcVISION control board, the most complex transformations can be specified, and it facilitates the mapping of the mainframe copybooks, redefines, data dictionaries, data catalogs, codepages, data type mapping, and more via the user-friendly interface. The repository editor allows users to control data transformations.

What is Confluent?

Confluent Cloud is a real-time data in motion platform that can be deployed in any public cloud, in any region of your choice. It comes with an SLA and uptime of 99.95%, and fully managed components like ZooKeeper, Kafka brokers, 120+ Kafka connectors, Schema Registry, and ksqlDB so you can leverage it on any cloud without having to worry about how it runs and scales.

Kafka Connect, Connect API, connectors, and tcVISION IBM Db2 connector

Kafka comes with three core APIs:

  • Kafka producer/Consumer API
  • Connect API
  • KStreams API

Kafka Connect is a tool for scalably and reliably streaming data between Kafka and other data systems. It makes it simple to quickly define connectors that move large data sets into and out of Kafka. Kafka Connect can ingest entire databases or collect metrics from all your application servers into Kafka topics, making the data available for stream processing with low latency. Kafka Connect connects APIs under the hood with fully managed connector support in Confluent Cloud.

Step-by-step guide on how to use tcVISION and Confluent

This example discusses the integration of tcVISION replication of data from Db2 to Confluent Cloud.

Set up tcVISION access to Confluent

Create an account with Confluent to make a Confluent user ID/password; the user ID is generally your email address. To sign on to Confluent, go to the Confluent Cloud login and enter your user ID:

Confluent Cloud welcome page

Then, enter your password:

Enter your password

When you log in, you’ll be in a Confluent environment called “default”:

Confluent environment called “default”

A Confluent environment is a type of container that holds clusters which in turn hold topics. If you are familiar with messaging systems, Confluent/Kafka will seem familiar. A cluster will need to be created to serve as a target for the data produced by tcVISION. The first attribute to be selected is the type of cluster. Confluent offers three types: Basic, Standard, and Dedicated. For the purposes of this demonstration, Basic will be used. A Basic cluster does not incur charges for simply existing, but does for data transmission and data storage.

Select "Basic cluster" and begin configuration

Select Begin configuration.

Select a cloud provider

Here, a cloud provider can be chosen—AWS, Google Cloud, or Microsoft Azure. For this example, AWS is used. Select Continue and the characteristics of the new cluster are displayed, which we’ve named “tcVISION_cluster_0”:

Cluster characteristics

After entering your payment information (not shown), you can click on the cluster name to launch the cluster overview.

Cluster overview

In order to use Confluent with tcVISION, the user must provide tcVISION with information about the cluster they intend to use. Specifically, the user must supply the hostname and port of the Confluent AWS virtual machine, and the credentials needed to access the cluster.

Confluent refers to the hostname and port as a bootstrap server. There can be multiple bootstrap servers for the purpose of load balancing, but a single server is used for this demonstration.

To find bootstrap server information, click Cluster Settings on the left-hand side:

Cluster settings

The bootstrap server will be listed under “Identification,” and includes both the AWS hostname and the port.

Credentials in Confluent consist of an API Key and an API Secret. These are generated for the cluster and take the place of the Confluent user ID and password used to log in. To generate a key/secret pair, click API Access on the left:

API Keys page

Followed by Create Key:

Select API Key scope

For this example, we use “Global Access” here, so click Next:

API Key and secret

Pay particular attention to the tip about saving the key and secret somewhere safe, because once this panel is exited, there is no way to display the secret again. A descriptive string for this key/secret pair can be filled in. The key or secret text to be copied can be selected, or use the convenient icons at the end of the field to copy. Once the key/secret has been safely stored, check the box that says it has been done, and click Save. You will return to the “API Keys” panel, and the key is now displayed:

API Key displayed

Set up Confluent and define the topic

The last thing to do is define a topic within the cluster. Confluent producers have the capability to define their own topics within a cluster, but this capability can be disabled by a Confluent configuration and is disabled in the configuration used here.

Go back to the cluster Overview:

Cluster Overview

On the left sidebar, click Topics:


Then Create Topic:

Create a topic

The topic name is filled in (“CONFLUENT_CLOUD_TOPIC1”), overriding the number of partitions from 6 to 1, since that is what the Confluent demo uses. Click Create with defaults:

Cloud topic

A topic is now available, which can be populated with Db2 data.

Set up tcVISION and run a bulk load of Db2 data

tcVISION’s control board is a Windows graphical user interface (GUI) that allows users to configure the replication stream between various database platforms, including the IBM mainframe and Confluent. Using the control board and built-in wizards, users can define the metadata and the mappings between the mainframe and target.

The following sequence of screens shows the steps required to create the tcVISION metadata and scripts for replicating mainframe Db2 z/OS data to Confluent.

Access the tcVISION control board:

tcVISION control board

Log on to Db2 z/OS:

Db2 z/OS

Create metadata that is specific to the input (Db2) and output (Kafka) and the replication definition. In this example, the Db2 table is mapped to the Confluent Cloud Kafka topic using JSON:

Import of structure definitions

The tcVISION metadata wizard asks for the information required for the replication of the mainframe database to Confluent Cloud. For Db2 z/OS, it asks for the mainframe Db2 subsystem:

Source type for structure definition import

Db2 subsystem

tcVISION presents the tables contained in the Db2 z/OS catalog on the mainframe. Select the schemas and associated tables for replication:

Select the schemas and associated tables for replication

Once the required tcVISION wizard-based screens are completed, the tool automatically defines the mappings between the source and target. tcVISION’s metadata import wizard creates a default mapping that handles data type conversion issues, such as EBCDIC to ASCII, Endianness conversion, codepages, redefines data types, and more:

Default mapping

tcVISION data scripts are created through wizards. Data scripts control the replication of data from the source (Db2 z/OS) to the target (Confluent Cloud Kafka JSON). tcVISION bulk load scripts are a type of data script that performs the initial load of the Kafka topic. The following script shows data being accessed directly from the mainframe Db2 z/OS database. Another alternative to reduce MIPS consumption is to read the data from a Db2 image copy.

Data script

Bulk load script running:

Bulk load script running

After execution of the bulk load script, replication statistics of the Db2 bulk load into the Confluent Cloud Kafka topic can be viewed:

Replication statistics of the Db2 bulk load

Now that the topic has been loaded with data from Db2, it can be displayed in Confluent. To do this, navigate to the topics panel again:

Notice that there are now statistics indicating that the tcVISION producer uploaded some data to the topic. On the horizontal menu, switch from “Overview” to “Messages” to display the messages (data records) that the tcVISION bulk load placed in the topic. The display can be filtered in various ways, but for this example, the default is used: “Jump to Offset,” which says “start displaying sequentially from this offset.” Here, an offset of 0 (start at the beginning) is specified, since we just want to verify that the Db2 data uploaded by tcVISION was actually delivered:

Messages (data records) from tcVISION bulk load

Run a change script in tcVISION to show the changes in Confluent

To capture ongoing changes to Db2 in real time, a Db2 z/OS CDC replication script is created.

This script captures the changes on the Db2 z/OS side and applies them into the repository where the output target is Confluent Cloud topic.

Replication script

Replication script

Target database Confluent Cloud topic

The CDC replication is initiated from the tcVISION control board. The tcVISION control board shows a graphical representation of the replication:

Graphical representation of the replication

The CDC replication is now actively capturing and replicating data changes whenever they occur on the Db2 z/OS side. You can test it by making a change in the Db2 z/OS table:

********************************* Top of Data **********************************
UPDATE SXE1.TVKFKATB                                                    00010004
SET DEPT = '696969'                                                     00040029
WHERE PERS_ID = 5;                                                      00050004
DSNE615I NUMBER OF ROWS AFFECTED IS 1                                           
--COMMIT;                                                               00060019
DSNE617I COMMIT PERFORMED, SQLCODE IS 0                                         
DSNE620I NUMBER OF SQL STATEMENTS PROCESSED IS 1                                
DSNE621I NUMBER OF INPUT RECORDS READ IS 4                                      
DSNE622I NUMBER OF OUTPUT RECORDS WRITTEN IS 17                                 
******************************** Bottom of Data ********************************

This change is processed and replicated by tcVISION. The tcVISION control board shows the statistics highlighting that one update was performed:

Display of extended statistics

Checking in Confluent, the Db2 z/OS change has successfully been propagated to the Confluent Cloud topic:

Db2 z/OS change successfully propagated to Confluent Cloud topic

tcVISION and Confluent are better together

With tcVISION’s groundbreaking Db2 CDC connector and Confluent’s ability to serve as the multi-tenant data hub, this combination creates a very powerful solution to aggregate data from multiple sources and have data published into various Kafka topics. Sourcing events from any kind of Db2 via a connector into Confluent will set data in motion for the entire organization. Simplicity and agility are key elements of the tcVISION and Confluent “better together” story.


Video: tcVISION Demonstration…

In this video, we show a tcVISION overview, then a demonstration of replication of mainframe data on AWS RDS for PostgreSQL:

Contact Treehouse Software for a tcVISION Demo Today!

No matter where you want your mainframe data to go – the Cloud, open systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software tcVISION Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Treehouse Software Customer Success: ETS uses tcVISION for Real-Time Synchronization Between their Mainframe IDMS Data and AWS RDS for PostgreSQL

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software, Inc.


This blog focuses on a current Treehouse Software customer – ETS. Headquartered in Princeton, New Jersey, ETS is a private, nonprofit organization with approximately 3,000 employees devoted to educational measurement and research. ETS develops and administer a broad range of educational products and services for government agencies, academic institutions and corporations, including the TOEFL® and TOEIC® tests, the GRE® General and Subject Tests, and the Praxis® assessments. At nonprofit ETS, our belief in the life-changing power of learning is at the root of everything we do — it’s behind the tools we develop to move learning forward, the research that inspires educational progress and the commitment we make to enable opportunity for learners everywhere. We’re with you on the journey to what’s possible.

Business Background

ETS products and services are available to institutions, businesses, organizations and governments in more than 180 countries around the world. The top industries served by ETS are K–12 Education, Higher Education, English-language Learning, Career Development, and Consulting Services.

Business Issue

Most of ETS’s high volume critical application data is stored on an IBM mainframe in IDMS databases.  The technology is very old, therefore it is difficult to recruit and retain qualified technical personnel to maintain applications.  ETS is moving to Cloud-based computing which will allow them to retire the mainframe environments and modernize the applications.  The data is used and shared across several applications.  ETS required a solution that would allow them to continue, uninterrupted, daily operations on their mainframe while replicating data to their AWS Cloud platform, where they could develop modern application features.  This solution enables ETS to maintain demanding daily processing while they modernize and develop innovative Cloud solutions to meet and exceed customer requirements.

The Technology Solution


Treehouse Software and the ETS team developed a rigid testing plan to implement tcVISION and performed a Proof of Concept to measure the effectiveness of the data replication, considering the high volumes of data changes on the source databases.  We collaborated on architecture requirements and installation steps.  There were many considerations associated with this process, including monitoring, alarming, configuration options, high availability, measuring the impact to existing mainframe database performance, restart capability, and security.  Concurrently, a team of subject matter experts worked on data mappings and translation of database designs from the IDMS network databases to AWS PostgreSQL relational databases.  The goal was to be able to replicate two very large IBM mainframe IDMS databases real-time on two Cloud-based PostgreSQL databases. Implementation was done in phases, starting with one non-production database being replicated to the Cloud.  High-volume testing was performed on the source database to simulate peak processing, replicating millions of transactions to the target PostgreSQL databases.  Many technical challenges were encountered and resolved with outstanding technical assistance from the Treehouse Software support team.  Once in production, the tcVISION product was able to deliver real-time data to the Cloud platform with no interruptions to the customer’s daily processing. The customer was then able to develop modern application features and functions in the Cloud to achieve independence from the legacy mainframe systems.  Using new Cloud-based capabilities enabled the customer to be more agile with meeting new requirements.


Video: tcVISION Demonstration…

In this video, we show a tcVISION overview, then a demonstration of replication of mainframe data on AWS RDS for PostgreSQL:

Contact Treehouse Software for a tcVISION Demo Today!

No matter where you want your mainframe data to go – the Cloud, open systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software tcVISION Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Treehouse Software Customer Case Study: A Large Airline’s Real-time Data Synchronization Between IBM Mainframe Adabas and Oracle RDBMS

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software, Inc.


This blog focuses on a current Treehouse Software customer – a major airline that is a long-time user of Software AG’s Adabas database on their mainframe system.

Business Background

This U.S. based airline is one of the largest domestic air carriers, and during peak travel seasons, they operate thousands of weekday departures within a network of hundreds of destinations in the United States and several other countries.

Business Issue

The airline’s IT modernization team was looking for a technology solution that enabled them to move their Adabas data off of the mainframe to more modern applications. However, their mainframe contains vital airline maintenance and parts data that must always be highly available, so rather than performing a complete migration from the mainframe, Treehouse technical representatives and the customer decided to utilize a data warehouse and real-time mainframe data replication. This architecture allows the mainframe legacy teams to maintain existing critical applications, while the modernization team develops applications on the newly created Oracle-based RDBMS. All teams at the airline determined that tcVISION real-time mainframe data replication was the perfect fit for meeting their goals.

The airline requires that tcVISION must support online and batch Adabas transactions and provide data replication between Adabas and their new Oracle RDBMS. Additionally, their large databases contain millions of rows (> 50 million) that must be supported, as well as support for database change audit requirements (datetime and type of operation), transaction management, and notification of exception events. There must also be support for configuration management between development, QA, and production.

The tcVISION Technology Solution...

The following is a high-level view of the airline customer’s tcVISION data replication architecture:


  • Adabas: Mainframe data source containing business critical information replicated to the RDBMS.
  • Oracle: Open Platform RDBMS chosen by customer as replication target for both data warehouse and modernization project. The tcVISION Manager also uses Oracle as a repository for the metadata (field mappings).
  • tcVISION Manager: Software component deployed on both source and target systems. It is responsible for provisioning resources for:
    • Processing scripts
    • Metadata import
    • Scheduling
  • tcSCRIPT: Software component deployed on both source and target systems. It works in conjunction with the tcVISION Manager to:
    • Perform initial load of Adabas into Oracle
    • Ongoing near realtime CDC (Change Data Capture) and replication from Adabas to Oracle
    • tcSCRIPT processes data from:
      • Direct from the DBMS (initial load) or from DBMS extracts
      • Adabas Protection log (PLOG)
  • tcVISION Control Board: Software component deployed on a Windows machine which provides graphical user interface for a single point of control to administer the tcVISION environment:
    • Metadata import, creates metadata rules governing relationship between mainframe and open platform data structures
    • Replication rule maintenance
    • DDL creation
    • Creation of ETL and replication processes
    • Start, stop, and schedule replication processes

Customer Outcomes

All requirements were met by tcVISION, which led to a successful project implementation.  Here is a look at the customer’s reported outcomes and benefits:

Business Outcome Customer Benefit
Data warehouse is always in sync with Adabas using tcVISION data replication Improved timeliness and reliability of reporting data
Reduced usage of mainframe MIPS Reduced cost
All data required for modernization project was successfully replicated to target environment Increased business efficiently and agility


Contact Treehouse Software for a Demo Today…

No matter where you want your mainframe data to go – the cloud, open systems, or any LUW target – tcVISION from Treehouse Software is your answer.


Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Further reading:

Many more mainframe data migration and replication customer case studies can be read on the Treehouse Software Website.