Treehouse Software Customers are Looking Upwards to Mainframe-to-Cloud Data Replication

The search is on for a mature, easy-to-implement Extract Transform and Load (ETL) solution for migrating mission critical data to the cloud.

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Treehouse Software’s tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data migration for mainframe application modernization projects, and enabling 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.

Mainframe-to-Cloud Case Use Example…

BAWAG P.S.K. is one of the largest banks in Austria, with more than 1.6 million private and business customers and is a well-known brand in the country. Their business strategy is oriented towards low risk and high efficiency.

BAWAG was looking to reduce the load on their IBM mainframe and as a result, reduce costs. The project involved offloading data from their core database system to a less expensive system, in real-time, and to provide read access from that system to the new infrastructure. The primary motivator for this data migration was the constantly increasing CPU costs on the mainframe caused by the growing transaction load of online banking, mobile banking, and the use of self service devices.

BAWAG ultimately migrated their online banking application to the cloud using tcVISION. Realtime Event-handling, Realtime Analytics, Realtime Fraud Prevention are only a few of the use cases that the bank’s solution currently covers.

BAWAG_Diagram

The bank decided to use tcVISION to migrate z/OS DB2 data into a Hadoop data lake (a storage repository that holds raw data in its native format). 20 Million transactions were made within 15 minutes.

Cost Reductions Seen Immediately

BAWAG is now seeing a 35-40 percent reduction of the MIPS consumption for online processing during business hours. After hours, consumption is less, because it is mainly batch processing on the mainframe. Currently, a volume of approximately 30 GB changed data (uncompressed) is replicated from DB2 per day.

In addition to the primary usage scenario, BAWAG can also cover additional use cases. This includes real-time-event handling and 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 now very low.

Additionally, BAWAG plans to extend the use of tcVISION in the future, including implementation of real-time replication from ORACLE into the data lake.


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

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.

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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.

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.

Cloud-y … with a 100 Percent Chance of Data

cloud computing and downloading

by Wayne Lashley, Chief Business Development Officer for Treehouse Software

Along with three of my colleagues, I recently participated in the Treehouse exhibit at the Gartner Application Architecture, Development and Integration (AADI) event in Las Vegas. This is a conference where we have exhibited in the past, and I personally have attended several other times. In fact, I just learned that the DI in AADI no longer stands for “Data Integration”; this change was only made in the past couple of years, as in the past it was the data integration aspect that made the show particularly relevant to Treehouse.

Though data integration vendors such as Informatica, Pervasive and Adeptia—and Treehouse—were in attendance, their numbers seemed diminished over prior years. And while “Legacy Modernization” had an entire subject “track” a couple of years ago, a number of “name” LM vendors were notably absent this year, and the topic was only rarely represented in sessions.

But there was a predominant theme at the event, and its name is Cloud.

People have been talking about “Cloud” for years already, and it is a well-established concept with many dimensions and extensive implementations. And it’s probably familiar enough to The Branches readers that I won’t waste words describing it, other than to say that it is simply a way to offer computing services via the Internet without the subscriber—most Cloud offerings are subscription-based—knowing or caring what or where the physical implementation is.

Many people consider that Salesforce.com is the granddaddy of all Cloud services, and to my mind it popularized the term “Software as a Service” (SaaS). Evolutionary Technologies, Inc. (ETI), a long-standing player in the data integration field and a company that I have had a lot of contact with over the years, reinvented itself around 2005 as a SaaS company, in doing so placing the company on the leading edge of “aaS” providers and essentially defining an entirely new market space.

These days there are a number of other “aaS” genres competing for mindshare and dollars, the most dominant being “Platform as a Service” (PaaS). Once again, Salesforce.com seemed to define the space initially, but others such as Amazon and Google have since come to dominate it. Just this week I was invited to an event for Oracle partners where Oracle executives will present their concept for an Oracle Cloud PaaS. I recall a Microsoft Worldwide Partners Conference (WWPC) a couple of years ago where Microsoft kicked off its Azure Cloud platform. You don’t have to install Microsoft Office on your PC anymore; Office 365 runs in the Cloud.

Even legacy applications are getting the Cloud treatment: a company called Heirloom Computing has commenced offering a platform for running legacy COBOL applications in the Cloud.

Cloud has also entered popular culture and commodity services. There’s a TV commercial that I keep seeing advertising a Cloud-based service that automatically troubleshoots, tunes up and cleans up your PC.
In short, you’re nobody if you’re not in the Cloud.

D-for-“Data” may have morphed into D-for-“Development” in the AADI Summit name, but data replication, integration and migration remain very relevant in the Cloud age. Indeed, you can’t spell Cloud without a D.

To support provisioning of Cloud-based applications, there has to be a means for getting data from where it is now—often in mainframe-based legacy databases or relational databases on open systems, within a company’s internal IT infrastructure—to the Cloud facilities, be they public or private. This doesn’t happen by magic. We have recently been working in a customer implementation where Oracle and DB2 data are being replicated bidirectionally in a Cloud implementation using our tcVISION solution. Such a scenario posed a bit of a challenge for us in terms of licensing: the machines on which tcVISION is installed are not specifically known at a given point in time. So we had to adapt our licensing model to accommodate the new reality.

We expect to see continued growth and demand for our replication and integration solutions as Cloud offerings evolve and expand. Furthermore, we are working on a new Cloud-oriented solution in collaboration with Cloud platform providers. I have briefed several Gartner analysts on it, and their feedback has been encouraging. Check back to this space regularly for news on this exciting new Treehouse offering.