tcVISION Mainframe Data Replication Solution is Featured in the Microsoft Azure Architecture Center

tcVISION is a data replication solution that provides an IBM mainframe integration solution for mainframe data replication, data synchronization, data migration, and change data capture (CDC) to multiple Azure data platform services.

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Contact Treehouse Software Today…

Treehouse Software is the worldwide distributor of tcVISION, a software product that allows immediate data replication between many Mainframe sources and Cloud and Open Systems targets, enabling government, healthcare, supply chain, financial, and a variety of public service organizations meet spikes in demand for vital information. 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.

Treehouse Software Customer Success: BMF uses tcVISION for Real-Time Data Replication Between Mainframe Adabas and PostgreSQL

BMF_Building

The Bundesministerium der Finanzen (BMF) is Germany’s Ministry of Finance and establishes sustainable fiscal policy that ensures financial empowerment of the federal budget. From tax policy via development of federal budget, to regulation of national and international financial markets – for these and other fiscal and economic questions of principle, the BMF creates strategies and concepts, and implements them. The Federal Tax Administration is part of BMF, and controls not only the cross-border goods traffic, but acts against illegal employment and other crimes. The tax administration also imposes consumer taxes (e.g., energy and tobacco tax, car tax, etc.). Financial relations between federation, countries, and communities are also coordinated by BMF.

Department II (federal budget) is part of the German government in charge of establishing the budget and financial planning of the federation. Throughout the year, it monitors execution of the budget for eventual intervention (e.g., with a budget freeze, or supplementary budget). After closing the fiscal year, the budget and balance sheet will be presented. The budget is a supplement of the budget act, legally binding.

The central service organization of BMF is the Informationstechnikzentrum Bund – ITZBund (Information technic center).

BUSINESS BACKGROUND

Drawing up the budget is a yearly, highly time consuming, and formalized business process. All departments are involved in nearly every sub-process, and budgeting and financial planning is supported by the application, “Haushaltsaufstellung / Budgetgeneration”. Using the generated reports, various addressees/receivers are supported (e.g., German Federal Government, German Federal Parliament, Federal Council of Germany, finance department in BMF, the employees in the departments, and the public).

Technically, the budget plan of the federation is based on technologies, including the IBM Mainframe with z/OS running Adabas and Natural.

The challenge was to provide an environment for employees in all departments that enables them to do their work quickly, easily, and efficiently. In the BMF, users must have an editorless, end-user driven, and real-time creation of ready-to-print products. An informative description of the workflow is shown on the website of the BMF.

The federal budget is available as download, or one can directly navigate through the data using the online application.

BUSINESS ISSUE

Some time ago, BMF decided to re-engineer the application for budget planning and port it to Open Source. To guarantee a seamless transition, the first step is propagation of data out of Adabas on z/OS to PostgreSQL, concluding with permanent synchronization.

The difficulties of this task are the complexities of setting up data definitions for the data structures in Natural and the propagation of data from Adabas on z/OS to PostgreSQL.

TECHNOLOGY SOLUTION: tcVISION

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After an analysis of the project, Treehouse Software proposed creating an extension to tcVISION’s change data capture (CDC) functionality for integration, so that tcVISION could enable BMF to continue using the implemented data definitions in a format suitable for the RDBMS.

The extension was developed within a few days, and a two-day on premise test demonstrated the solution fit the requirements of BMF.

BMF can now provide its data definitions from Natural LDA to the extension of tcVISION, and after the transformation, onto the PostgreSQL load process for processing. Another advantage of the tcVISION solution is that when needed, other targets can be integrated for propagation of data from the mainframe (e.g., Kafka, which BMF indicated is a future target environment).

Additionally, bi-directional propagation can be added in budget planning when BMF is ready.

Data structures are held in LDA, because this provides the advantages of higher flexibility in development and the adaption of new requirements to the data definitions. If definitions would have to be ported manually, in part, to PostgreSQL, it would have been a much bigger and error-prone effort.

Subsequent changes to Adabas structures can now use tcVISION’s newly developed extension to easily regenerate and load the correct definitions to the RDBMS, and tcVISION completely covers the customer’s requirements for special usage of *PEs and *MUs.

After thorough preparation and extensive testing, the solution was released to selected users first, then made available to all users.

* PEs and MUs are special Adabas formats for definition of tables. PE = Periodic Group, MU = Multiple Value Field.


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

Providing a High Availability Framework for Mainframe-to-AWS Data Replication

by Dan Vimont, Cloud Solutions Architect at Treehouse Software, Inc.

tcV_HA_on_AWS

Treehouse Software customers are using tcVISION to enable mission-critical mainframe-to-AWS data replication pipelines.  Some of these production pipelines are providing vital near-real-time synchronization between source and target, and thus can’t afford any significant downtime in the event of failure.  So it’s only natural that a number of our customers have been asking for advice in setting up a high availability configuration for their tcVISION components that run on AWS EC2 instances.  The High Availability Framework discussed here provides for a Failover EC2 instance to automatically pick up tcVISION processing should the Primary instance (running in another Availability Zone) go down.

The Core Components:  Primary Instance & Failover Instance

The core components of a tcVISION high availability framework consist of two EC2 instances running in different Availability Zones:  a Primary EC2 instance and a Failover EC2 instance.  Both identically-configured EC2 instances are attached to a shared working-storage file system (either an EFS or FSx volume), which allows the Failover instance to seamlessly and quickly pick up tcVISION processing should the Primary instance suddenly become unavailable.

HA1

Use a Step Function to Automate the Failover Process

In the event of failure of the Primary instance, the recommended framework calls for automatic triggering of a Step Function for reliable failover processing, with steps that include the following:

  • verify that the Primary instance is unavailable (The tcVISION service cannot be active on both instances simultaneously, so this verification is vital.)
  • redirect all network traffic from the Primary instance to the Failover instance (via Route 53)
  • start tcVISION processing on the Failover instance

HA2

When Ready, Use a Step Function to Automate the Restoration Process

After operations personnel have completed recovery of the Primary EC2 instance, another Step Function may be manually triggered to reliably transfer tcVISION processing back to the Primary instance.

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Many More Details are Available Upon Request to Treehouse Customers

Full details regarding our recommended High Availability Framework for tcVISION are available upon request to Treehouse customers.  AWS services utilized in the complete recommended framework include Step Functions, Lambda Functions, EventBridge rules, CloudWatch alarms, SNS topics, a Route 53 Private Hosted Zone, and more.  The following diagram is a partial visual inventory of the recommended framework components.

HA5

Interested in seeing a live, online demo of tcVISION?

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.


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How to Synchronize Data in Real Time Between the Mainframe and AWS with Treehouse Software’s Enterprise CDC Tool

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

Bidirectional_Data_Replication

Many mainframe integration scenarios require continuous near-real-time replication of relational data to keep a copy of the data synched in the Cloud. Change Data Capture (CDC) is used for this near-real-time transactional replication by capturing change log activity to drive changes in the target dataset.

Just what is CDC anyway?

Simply put, and in relation to Mainframe-to-Cloud and open systems data replication, CDC is the use of processes to identify when data has been changed in a source system, so the replicated upstream or downstream (depending on how you look at it) target can be kept in sync with the changes.

In a recent AWS Architecture Blog, readers learn about integration using mainframe data to build Cloud native services with AWS, including transactional replication-based integration via CDC.

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As mentioned in the blog, AWS Partner CDC Tools are available for connecting data center mainframes to the various data targets, and Treehouse Software’s tcVISION is one of those tools available in the AWS Marketplace.

tcVISION allows changes occurring in any mainframe application data to be tracked and captured, and then published to a variety of target AWS databases and applications. tcVISION provides an easy and fast approach for Hybrid Cloud projects, enabling real-time and bi-directional data replication between the hardware and AWS.

Example of Db2-to-AWS CDC using tcVISION Mainframe Manager:

tcVISION_Db2_To_AWS_CDC

tcVISION supports several CDC methods available, depending on each customer’s use case:

Bulk Transfer

  • Efficient transfer of entire databases
  • Analysis for data consistency (verification)
  • Initial load (ETL) and periodic mass data transfer
  • One-step data transfer

Log Processing

  • Transfer of changed data near-realtime or scheduled time frame
  • Reads both active logs and archived logs

Batch Compare

  • Comparison of data snapshots using checksums
  • Efficient transfer of changed data since last processing
  • Flexible processing options (SORT etc.)
  • Automatic creation of deltas by tcVISION

DBMS Extension

  • Real-time capture of changed data directly from the DBMS
  • Secure data storage even across DBMS restart
  • Flexible propagation methods

Interested in seeing a live, online demo of tcVISION CDC?

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.


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Treehouse Software Customer Case Study: A State Government Agency’s Real-time Data Synchronization Between IBM Mainframe Adabas and AWS

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

Mainframe_to_AWS_Graphic

Software AG’s Adabas is a mainframe database that is still heavily used by government sites throughout the U.S. and the world, and this blog focuses on a current Treehouse Software customer – a U.S. State Government Agency that uses Adabas on their mainframe system.

Business Issue

The Agency’s modernization team was looking for a Change Data Capture (CDC) technology solution that enables them to synchronize their mainframe Adabas data on AWS, particularly an Amazon RDS. As with most Treehouse customers, the State’s mainframe contains vital data that must always be highly available, so rather than attempting a complete migration from the mainframe, the modernization teams decided to implement a multi-year data replication plan. This allows the mainframe legacy teams to maintain existing critical applications, while the modernization team develops new applications on AWS.

After researching various technologies, the Agency discovered tcVISION on the AWS Parter Network Blog and contacted Treehouse Software to discuss their project and to see a demonstration of Mainframe-to-AWS data replication.

Addressing the Uniqueness of Adabas

Having specialized in tools and services complementary to Adabas/Natural applications since 1982, Treehouse Software has successfully encountered and addressed many unique scenarios within the Adabas environment. The Treehouse technical team documented three primary issues with Adabas/Natural that the Agency needed to consider when they began planning data replication on AWS:

  1. Adabas has no concept of “transaction isolation”, in that a program may read a record that another program has updated, in its updated state, even though the update has not been committed.  This means that programmatically reading a live Adabas database—one that is available to update users—will almost inevitably lead to erroneous extraction of data.  Record modifications (updates, inserts and deletes) that are extracted, and subsequently backed out, will be represented incorrectly—or not at all—in the target. Because of this, at Treehouse we say “the only safe data source is a static data source”—not the live database.
  2. Many legacy Adabas applications make use of “record typing”, i.e., multiple logical tables stored in a single Adabas file.  Often, each must be extracted to a separate table in the target RDBMS.  The classic example is that of the “code-lookup file”.  Most shops have a single file containing state codes, employee codes, product-type codes, etc.  Records belonging to a given “code table” may be distinguished by the presence of a value in a particular index (descriptor or superdescriptor in ADABAS parlance), or by a range of specific values.  Thus, the extraction process must be able to dynamically assign data content from a given record to different target tables depending on the data content itself.
  3. Adabas is most often used in conjunction with Software AG’s Natural 4GL, and “conveniently” provides for unique datatypes (“D” and “T”) that appear to be merely packed-decimal integers on the surface, but that represent date or date-time values when interpreted using Software AG’s proprietary Natural-oriented algorithm. The most appropriate way to migrate such datatypes is to recognize them and map them to the corresponding native RDBMS datatype (e.g., Oracle DATE) in conjunction with a transformation that decodes the Natural value and formats it to match the target datatype.

The tcVISION Technology Solution...

Adabas_To_AWS

After technical discussions and a successful proof of concept (POC) that proved out a set of use cases, all teams at the Agency determined that tcVISION real-time mainframe data replication capabilities were the perfect fit for meeting their goals.

tcVISION‘s modeling and mapping facilities are utilized to view and capture logical Adabas structures, as documented in Software AG’s PREDICT data dictionary, as well as physical structures as described in Adabas Field Definition Tables (FDTs).  Given that PREDICT is a “passive” data dictionary (there is no requirement that the logical and physical representations agree), it was necessary to scrutinize both to ensure that the source structures were accurately modeled.

Furthermore, tcVISION generates appropriate mappings and transformations for converting Adabas datatypes and structures to corresponding target datatypes and structures, including automatic handling of the proprietary “D” and “T” source datatypes.

The teams examined the three ways that tcVISION can access Adabas data:

  1. ETL – read the active database nucleus
  2. ETL – read datasets containing unloaded Adabas files created by the ADAULD utility
  3. CDC – read the active and archived PLOGs datasets

It was decided to access the data by reading the active and archived PLOGs datasets. The schema, mappings, and transformations from the metadata import were tailored to the customer’s specific requirements.  It is also now possible to import an existing RDBMS schema and retrofit it, via drag-and-drop in tcVISION, to the source Adabas elements.

Additionally, the Agency’s teams are very pleased with tcVISION‘s minimal usage of mainframe resources. The product’s “staged processing” methodology accomplishes this, whereby the only processing occurring on the mainframe is the capture of changes from Adabas PLOGs. The bulk of the processing occurs on the AWS side, minimizing tcVISION’s footprint on the mainframe as seen in this diagram:

tcVISION_Staged_Processing

The user defines on which platform stage their processing should be done. Do as little as possible on the mainframe: Stage 0 – capture data and send data (internal format) to target, and process data in Stages 1 – 3 in AWS.

Customer Outcome

All requirements were met by tcVISION, which led to a successful project implementation.


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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.


Further reading:

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

How to Replicate Mainframe Data on Azure SQL with tcVISION from Treehouse Software

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

tcVISION allows enterprise customers to replicate data between mainframe, Cloud, or Hybrid Cloud while maintaining their legacy environments.

We are currently working with a government site to architect bi-directional mainframe data replication on Azure SQL.  One of the customer’s requirements is for tcVISION to provide real-time data synchronization of changes on either platform reflected on the other platform (e.g., a change to an Azure SQL table is reflected back on mainframe). This way, the customer can modernize their application on the Azure Cloud without disrupting the existing critical work on their legacy system.

tcVISION_Azure_Architecture

VIDEO: See how tcVISION easily connects mainframe systems to Azure SQL…

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

Azure SQL is a supported target in tcVISION, and in this instructional video, tcVISION is shown synchronizing data in real-time between Db2 on z/OS and Azure SQL:


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Contact Treehouse Software 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.

Why is High Availability so Important for Mainframe Data Modernization on the Cloud?

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

Many customers embarking on Mainframe-to-Cloud data replication projects with Treehouse Software are looking at high availability (HA) as a key consideration in the planning process. All of the major Cloud platforms have robust HA infrastructures that keep businesses running without downtime or human intervention when a zone or instance becomes unavailable. HA basic principles are essentially the same across all Cloud platforms.

In this blog, our example shows how the AWS Global Infrastructure and HA is architected with Treehouse Software’s tcVISION real-time mainframe data replication product. A well planned HA architecture ensures that systems are always functioning and accessible, with deployments located in various Availability Zones (AZs) worldwide.

The following example describes tcVISION‘s HA Architecture on AWS. During tcVISION ’s Change Data Capture (CDC) processing for mainframe data replication on the Cloud, HA must be maintained. The Amazon Elastic Compute Cloud (Amazon EC2), which contains the tcVISION Agent, is part of an Auto Scaling Group that is spread across AZs with Amazon EC2 instance(s).

tcVISION and AWS overall architecture…

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Upon failure, the replacement Amazon EC2 instance tcVISION Agent is launched and communicates its IP address to the mainframe tcVISION Agent. The mainframe tcVISION Agent then starts communication with the replacement Amazon EC2 tcVISION Agent.

Once the Amazon EC2 tcVISION Agent is restarted, it continues processing at its next logical restart point, using a combination of the LUW and Restart files. LUW files contain committed data transactions not yet applied to the target database. Restart files contain a pointer to the last captured and committed transaction and queued uncommitted CDC data. Both file types are stored on a highly available data store, such as Amazon Elastic File System (EFS).

tcVISION and AWS HA architecture…

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For production workloads, Treehouse Software recommends turning on Multi-AZ target and metadata databases.

To keep all the dynamic data in an HA architecture, tcVISION uses EFS, which provides a simple, scalable, fully managed elastic file system for use with AWS Cloud services and on-premises resources. It is built to scale on-demand to petabytes without disrupting applications, growing and shrinking automatically as you add and remove files, eliminating the need to provision and manage capacity to accommodate growth.

More information on AWS HA


Treehouse Software helps enterprises immediately start synchronizing their mainframe data on the Cloud, Hybrid Cloud, and Open Systems to take advantage of the most advanced, scalable, secure, and highly available technologies in the world with tcVISION

tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data replication for mainframe application modernization projects and enabling bi-directional data replication between mainframe, Cloud, Open Systems, Linux, Unix, and Windows platforms.

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Contact Treehouse Software for a Demo Today…

Just fill out the tcVISION Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your tcVISION demonstration. This will be a live, on-line demonstration that shows tcVISION replicating data from the mainframe to a Cloud target database.

Quickly Begin Replicating Mainframe Data on Cloud and Open Systems During a tcVISION Proof of Concept.

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

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Customers can start moving mainframe data within days during a tcVISION POC…

An online tcVISION Proof of Concept (POC) is approximately 10 business days, with the customer providing a representative subset of data, use cases, and goals for the POC. A Treehouse Software consultant will assist in downloading and installing tcVISION, and conduct a limited-scope implementation of a tcVISION application. This application uses customer data and executes on customer facilities, in a non-production environment. A document is provided beforehand that outlines the requirements and agenda for the POC.

By the end of the POC, customers can begin replicating mainframe data to their Cloud or Open Systems target database.  It can happen that fast!.

About tcVISION

More Cloud, Open Systems, and Systems Integration partners are recommending tcVISION, Treehouse Software’s Mainframe-to-Cloud data replication product for modernization projects. tcVISION focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud and Open System databases and applications. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to a variety of RDBMS and other targets.

tcVISION_Overall_Diagram_Cloud_OS

Further reading…

Treehouse Software is an AWS, Google Cloud, and Microsoft Technology Partner, and the AWS Partner Network published a blog about tcVISION, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms.


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Contact Treehouse Software for a tcVISION Demo Today…

Simply fill out our Product Demonstration Request Form and a Treehouse representative will be contacting you to set up a time for your requested demonstration.

Treehouse Software’s Differentiator: Enterprise Mainframe Expertise Since 1982

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

Treehoue_Mainframe_Experience

This blog explores Treehouse Software‘s decades worth of experience in helping mainframe customers with innovative tools, services, and training. 

When Treehouse Software began in 1982, the business focused on software that was complementary to the Software AG mainframe product line (Adabas database management system and Natural programming language) in the areas of security, control, auditing, performance enhancement, etc.

In more recent years, Treehouse Software has become a global leader in providing solutions for real-time and bi-directional data replication between a variety of mainframe and non-mainframe sources, including (Mainframe): Adabas, Db2, VSAM, IMS, CA Datacom, and CA IDMS; and (Non-mainframe): Amazon Web Services (AWS), Google Cloud, Microsoft Azure, PostgreSQL, Kafka, Oracle, Microsoft SQL Server, IBM Db2 LUW and Db2 BLU, IBM Informix, MongoDB, Hadoop, and many more. Here is our list of supported data sources and targets.

Decades Worth of Mainframe Knowledge…

When asked by prospective customers, “What are your primary differentiators?”, we can be tempted to first talk about superior product features and capabilities, but in addition to our exceptional products, it is Treehouse Software’s depth of knowledge and experience in the mainframe world that is the real game changer.

Most mainframe users face critical data management challenges due to the complexity and proprietary nature of deeply entrenched databases on the platform. Our extensive experience, deep knowledge, and wide-ranging capabilities in mainframe technologies make the company a valued partner for third-party solution providers and a trusted advisor to customers.

Treehouse Software’s visionary leadership in this market has included pioneering Adabas-to-RDBMS ETL and CDC with tRelational/DPS in the mid-1990s.  Today, Treehouse Software stands alone in its product maturity, and capability, including expanded capabilities with the tcVISION product, which enables migration and synchronization of virtually any mainframe or non-mainframe database or data source.

Despite the rapid pace of change in the IT landscape, Treehouse Software’s customer base can be assured that there remains a strong commitment to providing continued support and upgrades for the product suite.

Treehouse Software provides tools and expertise for the riskiest and most-often overlooked parts of modernization and integration projects – data migration and integration.   Tapping into the vast experience of Treehouse’s technicians, and using proven products and services eliminates reliance on end-customer programming staff to write and maintain data extracts and middleware. Treehouse Software’s know-how reduces cost and mitigates risk in legacy modernization initiatives, where data migration and integration complexity is often underestimated, yet critical to success.

Our Mainframe Experts are Our Best Assets

We are fortunate to have a staff with a wealth of knowledge and skills that span not only Mainframe, but Cloud, LUW, and Open Systems technologies. Whether a customer wants to move data from their mainframe platform to other on-premises open systems or LUW databases, or to the Cloud (e.g., AWS, Google Cloud, Azure, etc.), Treehouse Software has the technical expertise and support needed to ensure successful project completion.

Treehouse Software‘s technicians have installed products and trained end-users in some of the largest mainframe sites around the world.  Mature, robust, and reliable, these products are also backed by our highly-rated 24X7 technical support.

The Treehouse Team Approach

TechniciansConnectivity

Treehouse Software has proven its ability to partner and work effectively as part of a larger team to solve client problems.  AWS, Google, Microsoft, Deloitte, Accenture, and other large vendors have selected our technology, services, and training for their mainframe data migration and application modernization practices.


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Contact Treehouse Software for a Product Demo Today…

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 product demonstration.

Treehouse Software is Helping Government Agencies with Mainframe Adabas Data Take Advantage of Cutting Edge Cloud-based Technologies

by Joseph Brady, Director of Business Development / Cloud Alliance Lead at Treehouse Software, Inc.

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Many government agencies have large volumes of mission critical and historical data stored in a variety of legacy mainframe databases (for this blog, we are focusing on Adabas). These government agencies combine a broad range human service programs, including employment assistance and job training, child and adult protection, child support enforcement, cash assistance, and services for the developmentally disabled, all of which constantly require accurate, up-to-date, and secure data.

To support the needs of clients, government agencies are generally broken into multiple divisions, including the division that Treehouse Software works with the most — Technology Services. The Technology Services divisions provide technical and systems services for the development, maintenance, and enhancement of automated business systems. They also ensure that the production and sub-production databases are running smoothly and efficiently by performing necessary maintenance of the databases.

Rapidly changing national health and economic conditions are making fast access to the most current information more important than ever for government agencies and the public.  As a result, a top priority for Technology Services divisions is modernizing critical data residing on long-standing mainframe databases. Unlocking the value of this important data can be difficult, because the data can be utilized by numerous interlinked and dependent programs that have been in place for many years, and sometimes decades.

Many Treehouse government customers are now looking for modernization solutions that allow their legacy mainframe environments to continue, while replicating data in real time on highly available Cloud-based platforms, such as AWS, Google Cloud, and Microsoft Azure. tcVISION from Treehouse Software allows a “data-first” approach, whereby immediate data replication to the Cloud helps government agencies begin strategies to meet spikes in demand for vital information, especially in times of crisis.

Just what is it about Adabas?

Adabas is a mainframe database that is still heavily used by government sites throughout the U.S. and the world. Having specialized in tools and services complementary to Adabas/Natural applications since 1982, Treehouse has successfully encountered and addressed many unique issues within the Adabas environment. This excerpt from a Treehouse technical document outlines three primary issues with Adabas/Natural that must be considered:

  1. Adabas has no concept of “transaction isolation”, in that a program may read a record that another program has updated, in its updated state, even though the update has not been committed.  This means that programmatically reading a live Adabas database—one that is available to update users—will almost inevitably lead to erroneous extraction of data.  Record modifications (updates, inserts and deletes) that are extracted, and subsequently backed out, will be represented incorrectly—or not at all—in the target. Because of this, at Treehouse we say “the only safe data source is a static data source”—not the live database.
  2. Many legacy Adabas applications make use of “record typing”, i.e., multiple logical tables stored in a single Adabas file.  Often, each must be extracted to a separate table in the target RDBMS.  The classic example is that of the “code-lookup file”.  Most shops have a single file containing state codes, employee codes, product-type codes, etc.  Records belonging to a given “code table” may be distinguished by the presence of a value in a particular index (descriptor or superdescriptor in ADABAS parlance), or by a range of specific values.  Thus, the extraction process must be able to dynamically assign data content from a given record to different target tables depending on the data content itself.
  3. Adabas is most often used in conjunction with Software AG’s Natural 4GL, and “conveniently” provides for unique datatypes (“D” and “T”) that appear to be merely packed-decimal integers on the surface, but that represent date or date-time values when interpreted using Software AG’s proprietary Natural-oriented algorithm. The most appropriate way to migrate such datatypes is to recognize them and map them to the corresponding native RDBMS datatype (e.g., Oracle DATE) in conjunction with a transformation that decodes the Natural value and formats it to match the target datatype.

For discovery and analysis of legacy source data structures, tcVISION’s modeling and mapping facilities view and capture logical Adabas structures, as documented in Software AG’s PREDICT data dictionary, as well as physical structures as described in Adabas Field Definition Tables (FDTs).  Note that PREDICT is a “passive” data dictionary—there is no requirement that the logical and physical representations agree, so it is necessary to scrutinize both to ensure that the source structures are accurately modeled.

Furthermore, tcVISION generates specification and implementation of appropriate mappings and transformations for converting Adabas datatypes and structures to corresponding RDBMS datatypes and structures, including automatic handling of the proprietary “D” and “T” source datatypes.

There are three ways tcVISION can access Adabas data:

  1. ETL – read the active database nucleus
  2. ETL – read datasets containing unloaded Adabas files created by the ADAULD utility
  3. CDC – read the active and archived PLOGs datasets

It is important to note that the schema, mappings and transformations that result from metadata import can be tailored to any specific requirements after the fact.  It is even possible to import an existing RDBMS schema and retrofit it, via drag-and-drop, to the source Adabas elements.

Using the tcVISION Control Board, a Windows GUI interface, the most complex transformations can be specified. Source fields can be combined into a single column, decomposed into separate columns, and be subject to calculations, database lookups, string operations and even programmatic manipulation. Furthermore, mapping rules can be implemented to specify that data content from a source Adabas record be mapped to one or more target RDBMS tables—each with its own different structure, as desired—based on the data content itself. Target tables can even be populated from more than one source file.

tcVISION supports complex replication scenarios…

tcVISION_Complex_Replication_Scenarios

tcVISION GUI Control Board functions as a central point of administration…

tcVISION_Control_Board

Automatically apply target schema within the Control Board…

tcVISION_Target_Schema

It is impossible to discuss all the features and capabilities of tcVISION within a high-level overview.  Given the maturity, wealth of functionality and relative low cost of tcVISION, as compared to the effort, complexity and risk entailed in a “Do-It-Yourself”, solution there is no reason why a legacy renewal project should run aground on data migration.

tcVISION’s minimal footprint on the mainframe…

Customers are very happy with tcVISION‘s “staged processing” methodology, where the only processing occurring on the mainframe was the capture of changes from Adabas PLOGs. The bulk of the processing occurs on the target platform, minimizing tcVISION’s footprint on the mainframe as seen in this diagram…

tcVISION_Staged_Processing

The user defines on which platform stage their processing should be done. Do as little as possible on the mainframe: Stage 0 – capture data and send data (internal format) to target, and process data up to Stage 3 in receiving environment.

Moving forward with tcVISION…

Treehouse Software has been helping local, state, and federal government agencies with Adabas and Natural in the areas of data migration, security, control, auditing, performance enhancement, etc. for decades. Over the years, Treehouse has expanded its capabilities to address new requirements for modernizing legacy mainframe Adabas databases on various Cloud platforms. By using Treehouse Software’s tcVISION Mainframe-to-Cloud data replication product, our government customers are able to immediately utilize some of the most advanced Cloud tools and services in the world.

tcVISION enables government agencies to synchronize mainframe Adabas data with various highly available and secure Cloud databases, data warehouses. etc.. Additionally, bi-directional, real-time data synchronization will enable changes on either platform to be reflected on the other platform (e.g., a change to a PostgreSQL table is reflected back on the mainframe database). This allows governments to modernize  applications on Cloud platforms without disrupting the existing critical work on the legacy system, and modern tools can now be used in the new environment, greatly enhancing agility.

Replicating mainframe data on the Cloud can happen within days during a tcVISION Proof of Concept (POC)…

tcVISION_Overall_Diagram_General_Cloud01

An online tcVISION POC is approximately 10 business days, with the customer providing use case and goals for the POC. A Treehouse Software consultant will assist in downloading and installing tcVISION and conducting a limited-scope implementation of a tcVISION application. This application uses customer data and executes on customer facilities, usually in a non-production environment. A document is provided beforehand that outlines the requirements, use cases, and agenda for the POC.

By the end of the 10-day POC, customers can begin replicating mainframe data to their Cloud target database.  It can happen that fast!

Further Reading…

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Treehouse Software is an AWS Technology Partner, and the AWS Partner Network published a blog about tcVISION, our Mainframe-to-Cloud data replication product, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms:

https://aws.amazon.com/blogs/apn/real-time-mainframe-data-replication-to-aws-with-tcvision-from-treehouse-software/


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Contact Treehouse Software for a tcVISION Demo Today…

Simply fill out our Product Demonstration Request Form and a Treehouse representative will be contacting you to set up a time for your requested demonstration.