TREETIP: tcVISION now supports IAM Files – a solution of Innovation Data Processing

IAM

“The Innovation Access Method (IAM) is a transparent alternative to VSAM KSDS, ESDS, and (as a cost option) to AIX and RRDS files. The savings achieved over VSAM can vary, but IAM typically uses 40-80% less I/Os, 20-70% less CPU and 30-70% less DASD. Savings in batch elapsed times and online response times can range from 20-80%.“ (INNOVATION Data Processing)

Users of IAM files now have the possibility of replicating data into any DBMS and NoSQL DBMS systems in the distributed systems environment as well as into Cloud and Hadoop platforms in real-time with tcVISION. Thus, the latest technology can easily be used for Analytics and Business Intelligence. tcVISION also supports bidirectional synchronization between IAM files and DBMS in the distributed environment. Therefore data between Oracle, SQL Server, DB2 LUW, Informix, Adabas LUW can be synchronized in real-time without programming effort. The transparent integration of IAM files in a heterogeneous system environment can be easily and quickly implemented.

Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

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tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

tRelational / DPS Adabas-to-Oracle Success in South Africa

by Hans-Peter Will, Senior Technical Representative and Joseph Brady, Manager of Marketing and Technical Documentation at Treehouse Software, Inc.

Recently, Hans-Peter Will, Senior Technical Representative for Treehouse Software, traveled to South Africa to assist our partner Bateleur Software (pty) Ltd. with setting up a large public-sector customer’s data replication implementation using our Adabas-to-RDBMS tool set, tRelational / DPS (Data Propagation System).

Arriving in Johannesburg, Peter met with representatives from Bateleur and the IT Organization, where the key players discussed how tRelational / DPS was going to be used in the project. The customer initially wanted to populate sample data into Oracle, so Peter configured tRelational / DPS to process one of the smaller Adabas files to generate some data. He also recommended running an analysis with tRelational to determine whether the file contained a unique key. Peter took this opportunity to show the customer what other benefits they could realize out of the analysis information. Interestingly, they used a personnel file for analysis, and Peter was immediately able to show that 23 of the records had no gender entry and 180 of records had no surname. The customer was very pleased to see these revelations in the first analysis, and looked forward to identifying other data quality issues before commencing data replication.

Customer Replication Scenario with Treehouse Software Product Set…

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The next step was to build the target structure in accordance with the Oracle DBA’s requirements. The DBA had specified that all columns were to be defined as VARCHAR2, except the date information. After the first model was completed, DDL and DPS parameters were generated and a quick materialization of data accomplished the desired result.

At the subsequent kickoff meeting, Peter provided a complete tRelational / DPS overview and discussed the target structure with the attendees and the Oracle DBA. The rest of the day was spent doing Adabas file implementations, analysis and modeling.

Setup was then completed for transferring extracted and transformed Adabas data into the customer’s Windows environment. Adabas Vista is used, so that one logical Adabas file was actually split into two files stored on different Adabas databases, and the customer wanted to combine them into the same target table in Oracle. While there was no unique descriptor, it was discovered that three fields in combination would make a unique key, enabling the model to be created to combine data from the separate physical files into a single Oracle table.

The team proceeded with file implementation, modeling, mapping, DPS executions, and resolving data issues. Various issues that were encountered, like invalid tab characters within the data, negative personnel numbers, duplicates in unique keys (maintained by the application) and the need to add an extra column to the output. These issues were resolved quickly by the customer’s staff.

Within a day, all the files were materialized and the PLOG copy process was modified so that from that point forward, every PLOG copy would automatically be processed through DPS Propagation to update the RDBMS on the target Windows machine.

The next day, Peter was asked by the customer, “How many of the files have been processed so far?”. Peter was pleased to report that every file was processed and was propagating successfully. The happy customer remarked that they never had a project that was completed this far ahead of the deadline.

Throughout the project, Peter never personally laid hands on a customer keyboard, but instead sat with staff, effectively training them and handing over comprehensive knowledge of tRelational / DPS. The customer was very excited to learn that their personnel can now easily use the product set to do any remaining work on their own.

A few days later, we received an e-mail from Bateleur:

“I had a very pleasant meeting with the customer today. They used tRelational to reject the non-unique keys, reran the Materialization, and reran DPS plus update into Oracle. The month-end update of Oracle that was taking nearly three days to complete, now takes five Minutes! Everyone delighted!”

Bjørn (Sam) Selmer-Olsen, Managing Director, Bateleur Software (pty) Ltd


About Treehouse Software’s tRelational / DPS Product Set

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tRelational / DPS is a robust product set that provides modeling and data transfer of legacy Adabas data into modern RDBMS-based platforms for Internet/Intranet/Business Intelligence applications. Treehouse Software designed these products to meet the demands of large, complex environments requiring product maturity, productivity, feature-richness, efficiency and high performance.

The tRelational component provides complete analysis, modeling and mapping of Adabas files and data elements to the target RDBMS tables and columns. DPS (Data Propagation System) performs Extract, Transformation, and Load (ETL) functions for the initial bulk RDBMS load and incremental Change Data Capture (CDC) batch processing to synchronize Adabas updates with the target RDBMS.

Visit the Treehouse Software website for more information on tRelational / DPS, or contact us to discuss your needs.

TREETIP: Integrate Mainframe Data Sources In Your Big Data Initiatives

tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data migration for mainframe application modernization projects and enabling bi-directional data replication between mainframe, Linux, Unix and Windows platforms. This innovative technology offers comprehensive abilities to identify and capture changes occurring in mainframe and relational databases, then publish the required information to an impressive variety of targets, both on-premise and Cloud-based.

Analysts have observed that perhaps 80 percent of the world’s corporate data still resides on mainframes. So it’s no surprise that Bloor Research (http://www.bloorresearch.com/research/spotlight/big-data-and-the-mainframe/), notes that “it is necessary today to place the mainframe as a ‘first-class player’ in any enterprise Big Data strategy.”

In February 2017 we highlighted tcVISION’s support for replication to the leading NoSQL database MongoDB. MongoDB continues to increase in popularity as a back end for operational applications with real-time requirements.

tcVISION also supports analytics and “mainframe offload” Big Data use cases that generally leverage Hadoop HDFS and/or streaming data transport. With tcVISION, data from a wide variety of IBM mainframe data source can be quickly and easily replicated to Big Data targets, requiring minimal mainframe know-how and having minimal impact on the mainframe.

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Boost the return on investment for your Big Data initiatives using tcVISION!


Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

_0_tcVISION_Simple_Diagram

tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix, and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

TREETIP: tcVISION Allows for Surprisingly Innovative Uses

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Treehouse Professional Services consultants help Adabas / Natural customers in a variety of ways, including DBA services, performance tuning, change management implementation and training, and data replication planning and training. Our experience and long history of service to the Adabas / Natural community helps us create innovative solutions for our customers’ challenges.

Recently Treehouse Senior Technical Representative Chris Rudolph assisted a customer with a tricky data replication problem. The customer uses tcVISION to perform bi-directional replication between Adabas and an RDBMS during the phase-in of a new application. Unfortunately, the new application incorrectly updated certain columns in the RDBMS, which were then replicated to Adabas. The customer attempted to address the issue by running a series of ADASEL reports against the Adabas PLOG and manually checking for “bad” transactions, which was a very time consuming process that pulled the Adabas DBA away from her normal duties.

Chris explained that tcVISION could expedite the process by replicating all transactions for the Adabas file to a journal table capturing the “before” and “after” values of the problematic columns. The developers working on the new application could then identify invalid values, correct the application, and patch the data themselves. This also allowed the Adabas DBA to return to their normal duties.

The journal table now includes columns to display the “before” and “after” values of the corrupted column, Adabas transaction time, end transaction time, operation and Adabas userid. The customer’s developers immediately recognized immense value from being able to query the journal table to find bad data, patch the data, prove that corruption is no longer taking place, and verify that all corrupted instances of the data have been patched. Journal tables have been added for all replicated Adabas files, and the developers now rely on the journal tables for all of their data patches.


Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

_0_tcVISION_Simple_Diagram

tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Customer Success: tcVISION / Hadoop Integration

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BAWAG P.S.K. is one of the largest and most profitable banks of Austria with more than 1.6 million private and business customers and a well known brand in the country. The business strategy is oriented towards low risk and high efficiency. Business segments are Retail Banking and Small Business, Corporate Lending and Investments and Treasury Services and Markets. The center of the BAWAG P.S.K. business strategy is the offering of easy to understand, transparent and first-rate products and services which meet the requirements of the customers.

The BAWAG P.S.K. Bank für Arbeit und Wirtschaft and Österreichische Postsparkasse Aktiengesellschaft ” (P.S.K.), Vienna, operates their IT on the z/OS operating system. The corporate data is stored in DB2 databases. ORACLE is the database platform for the Open System environments. In relationship with another project P.S.K already had a client component of tcVISION installed. Magister Markus Lechner, Head IT Applications: “tcVISION was already in use and we had good experiences as far as functionally and support is concerned. Because we were in the planning process for the implementation of another project, we included tcVISION in the list of software solutions. The goal of this project has been the reduction of the load on the IBM mainframe and as a result the reduction of costs. The intention was to offload data from our core database system to a less expensive system in real-time and to provide read access from that system to the new infrastructure. The reasons for this were constantly increasing CPU costs on the mainframe because of the growing transaction load of the Online Banking, Mobile Banking, and Self Service devices. A large percentage of the load was caused by Read-Only-Transactions.” Markus Lechner: “After the tcVISION presentation, we arranged a Proof Of Concept. The important aspects of the POC were not only the functionality of tcVISION within the project but we also wanted to see whether our expectations would be met related to performance and CPU consumption on the mainframe. In addition to tcVISION, we also evaluated another product. All of our expectations have been met to our full satisfaction during the POC and we made the decision to go ahead with tcVISION.”

After a short implementation period, the project is now in production for one year. Markus Lechner describes the project: “The primary objective of the project with tcVISION was the reduction of CPU load on the mainframe to reduce our costs. Our intention was to offload data from our core database system to a less expensive system in real-time and to provide read access from that system to the new infrastructure.

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We use tcVISION for the realtime replication and we use Apache Hadoop as a cost efficient system for the storage of the data. In addition to the primary usage scenario we have the benefit to also cover additional use cases. This includes Real-time-EventHandling & Stream Processing, Analytics based upon real-time data as well as the possibility to report and analyze structured and unstructured data with excellent performance. The system can be inexpensively operated on Commodity Hardware and has no scalability limitations. Compared to the savings the costs of replication (CPU consumption) of tcVISION are very low. The support provided  was excellent during the implementation phase and also during the production phase. Inquiries by telephone or E-mail cause prompt reactions. Problems that came up during this period were solved as soon as possible even when the tcVISION software had to be extended.” There are additional plans to extend the use of tcVISION in the future. One is to implement real-time replication from ORACLE into the data lake.

Magister Markus Lechner draws a conclusion: “tcVISION enables us to significantly reduce our mainframe cost through a real-time replication to a less expensive environment. tcVISION performs a very economical log file based replication. In addition we are now in a position to implement numerous application cases based upon the replicated data which would have been too expensive and resource intensive on the mainframe. Realtime-Event-handling, Realtime-Analytics, Realtime-Fraud Prevention are only a few of the use cases that we currently cover.”


tcVISION

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tcVISION enables bidirectional replication for DB2, Oracle, and SQL Server running on Linux/Unix/Windows, and synchronizes each data source, first by doing a bulk load from source(s) to target and then by replicating only changes— only committed changes—from source(s) to target. So there can never be ambiguity as to whether a query against the target database involves uncommitted data.

Read other tcVISON customer success stories here.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Mainframe CDC from Treehouse Software

The globalization of markets, increase of data volumes, and high demand for up-to-date information require new data transfer and exchange solutions for heterogeneous IT architectures, and as many customers have discovered, Treehouse Software has the right product (or combination of products) to meet any conceivable mainframe data migration, replication, or integration requirement. To meet many of these needs, Treehouse Software’s proven and mature tcVISION product moves data – as little as possible – as much as necessary. tcVISION is an innovative software solution that processes changed data in real time, in intervals, or event based.

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The tcVISION solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and LUW databases and applications. Changes occurring in any mainframe application data are tracked and captured, and then published to a variety of RDBMS and other targets.

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tcVISION enables bidirectional replication for DB2, Oracle, and SQL Server running on Linux/Unix/Windows, and synchronizes each data source, first by doing a bulk load from source(s) to target and then by replicating only changes— only committed changes—from source(s) to target. So there can never be ambiguity as to whether a query against the target database involves uncommitted data.

Read some tcVISON customer success stories here.


Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

 

TREETIP: Did You Know About tRelational’s Schema Auto-Generation Feature?

by Joseph Brady, Manager of Marketing and Technical Documentation at Treehouse Software, Inc.

tRelational, the data analysis, modeling, and mapping component of Treehouse Software’s Adabas-to-RDBMS product set provides three options for developing RDBMS data models and mapping ADABAS fields to RDBMS columns:

Option 1: Auto-generation

Option 2: Importation of existing RDBMS schema elements

Option 3: Detailed definition and manipulation of schema and mapping elements using tRelational

The Auto-generation function can be an extremely useful productivity aid. By simply invoking this function and specifying an Adabas file structure, a fully-functional corresponding RDBMS schema (Tables, Columns, Primary Keys, Foreign Key relationships and constraints) and appropriate mappings are created virtually instantaneously. The table and column names, datatypes, lengths, and mappings/transformations are all automatically tailored specifically for the RDBMS product, platform, and version–the user need not be an expert in the RDBMS.

tRelational’s schema auto-generation simply requires specification of an Adabas file structure and associated options…

tRe_AutoGen

The auto-generated model can be immediately used to generate both RDBMS DDL and parameters for the Data Propagation System (DPS) component. Within minutes of identifying the desired Adabas file or files to tRelational, the physical RDBMS schema can be implemented on the target platform and DPS can begin materializing and propagating data to load into the tables.

It is important to note that these modeling options complement each other and can be used in combination to meet any requirements. Auto-generated schema elements can be completely customized “after the fact”, as can imported elements. Auto-generation can be used at the file level to generate complete tables and table contents at the field level, making it easy to then manually define and map one or more columns within a table, or even to denormalize MU/PE structures into a set of discrete columns.


About Treehouse Software’s tRelational / DPS Product Set

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tRelational / DPS is a robust product set that provides modeling and data transfer of legacy Adabas data into modern RDBMS-based platforms for Internet/Intranet/Business Intelligence applications. Treehouse Software designed these products to meet the demands of large, complex environments requiring product maturity, productivity, feature-richness, efficiency and high performance.

The tRelational component provides complete analysis, modeling and mapping of Adabas files and data elements to the target RDBMS tables and columns. DPS (Data Propagation System) performs Extract, Transformation, and Load (ETL) functions for the initial bulk RDBMS load and incremental Change Data Capture (CDC) batch processing to synchronize Adabas updates with the target RDBMS.

Visit the Treehouse Software website for more information on tRelational / DPS, or contact us to discuss your needs.