- IBM DB2
- IBM IMS/DB / DL1
- Software AG ADABAS
- CA IDMS/DB
- CA DATACOM/DB
- IBM DB2 LUW
- IBM BLU Acceleration
- IBM Informix
- IBM NETEZZA
- Microsoft SQL Server
tcVISION allows to sychronise data bidirectionally, loop-back prevention is integrated
Only committed data changes are captured. tcVISION interfaces with your existing security system.
Controlled data exchange
tcVISION provides many mechanisms to control data flow. This makes the data exchange revision-proof.
No Middle-ware necessary
tcVISION transfers data in “raw format” and compressed via TCP/IP. This makes it extremely fast.
If you want to keep multiple copies of data within your organization on the same platform i.e. z/OS or perhaps even across multiple platforms such as Mainframe, Unix, Linux or Windows then maintaining accurate and consistent data current across all of these copies makes it paramount that the data is synchronised in a fast and reliable fashion
Data Synchronisation is also a very efficient method of maintaining a backup copy of data or maintaining peer to peer disaster recovery sites. You may even have a requirement to create independent data files containing a mixture of data from various databases or data files scattered across multiple platforms this is particular useful when you have a requirement to create test data for sand boxes and mask sensitive data for testing purposes.
Especially important is that the system used has a very simple and easy to use interface that is robust and intuitive eliminating the guesswork and technical knowledge required to operate over multiple platforms and the myriad of databases and data structures typically used across today’s corporations.
If for instance a user on a Windows Platform is using data from a mainframe database then it would make sense to ensure that any updates or changes to this data are accurately propagated across all of your the platforms in a fast, reliable and consistent manner.
Also it is wise to understand your requirements fully such as knowing if you need to keep consistent data for example you may want to keep a backup of certain data at a particular point in time or even if you need to generate a one time report using selected data you may not need to synchronise this data by utilising two way data Synchronisation as one way data synchronisation may suffice.
For example: if you want to allow access to this data from a mobile device or maybe from a Linux system using z/OS data and you accept that this user can update or even delete this data then you would need to ensure that you are using a system to synchronisation this data that is both automatic and completely reliable without requiring programming effort or manual intervention as both would be fraught with danger.
This is where a product such as tcVISION is a very wise thing to use as it takes control of the whole process from start to finish. It’s not only a fully automatic system it does not require you to spend time and effort programming. A huge advantage to tcVISION is that it does not require any middle layers of software.
It is extremely robust and supports almost all data types and structures across multiple platforms and the hard work has already been done in ensuring that your data remains up to date and consistent across all of your platforms no matter what operating system or data structures you are employing across the enterprise in fact tcVISION supports more data types than any other like product.
Data Synchronisation with tcVISION easily allows for Data Replication for test or sandbox purposes or to clean data for data distribution.
The many features of tcVISION assist installations to more easily manage their data for data warehousing, real-time analytics, Big Data, Cloud data, business intelligence, & data quality management.
Efficient data handling for Unix data, Linux Data, Mainframe data, Oracle Data, db2 Data, and windows data as the software is more than capable to handle all the various file and data formats whether it be flat files or database files without the inherent problems or manipulating cross platform data and sharing data from multiple platforms and resources. See frequent questions.
For business intelligence and real-time analytics you can easily create input data for evaluation from multiple sources, platforms, and data types into a single input stream without having the technical knowledge of these file structures or types due to the extremely powerful user interface (the control panel) that does all the heavy lifting for the user making it easy and convenient to produce one off data files and output to any platform.
Here you can find out a lot more about tcVISION and it’s data synchronisation capabilities which is why it has been selected as the go to platform for many organizations that just cannot afford even once to be using data on any of their systems that may not be current in real time. For direct access to mainframe data from LUW systems see tcACCESS.
You can download brochures from our data synchronisation downloads page.
The tcVISION solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and LUW 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’s capture facilities detect changes in mainframe and other data sources without programming effort, and reduce the amount of data that must be transferred between systems to an absolute minimum.
tcVISION guarantees transparent, efficient and auditable data transfer between sources and targets, and provides powerful routines to perform efficient, reliable bulk transfers of data. The tcVISION solution focuses on changed data when transferring information between mainframe and LUW data sources.
tcACCESS is a transparent integration of mainframe data sources and mainframe programs into LUW applications using industry standards.
In a nutshell tcACCESS is a comprehensive software solution that enables two-way integration between IBM mainframe systems and client/server, Web and SOA technologies without the need for mainframe knowledge or programming effort.
tcACCESS is a proven platform that facilitates SQL-based integration of mainframe data sources and programs into LUW applications using industry standards such as SQL, ODBC, JDBC, and .NET. SQL queries to access mainframe data can be easily created using drag and drop techniques — no programming required.
Available for Windows, Linux and UNIX, depending on the cloud system.
Databases supported in cloud systems: IBM DB2 LUW, IBM BLU Acceleration, IBM Informix, IBM NETEZZA, Oracle, Sybase, Microsoft SQL Server, Software AG ADABAS LUW, PostgreSQL, Teradata, MongoDB, Flat File Integration, SAP Hana, EXASOL, MySQL / MariaDB, JSON / Avro, ODBC, Kafka, Hadoop Data Lakes, HDFS, CSV
Support of all Change Data Capture methods:
Data Synchronisation Areas of application: Real-time analytics, big data, data warehousing, reporting, business intelligence, data quality management, application modernization, work offload to reduce the mainframe’s workload, migration of data and systems, usage of cloud technologies, SOA, etc.
Data integration combine data from across your enterprise into meaningful and valuable information. tcVISION is a complete data integration solution that delivers trusted data from a variety of data bases and files from various operating platforms.
Data Duplication: – Controlled data exchange tcVISION provides many mechanisms to control data flow with the very efficient Efficient bulk transfer for Mass data transportation for initial load or cyclic data exchange.
Coexistency: – Synchronisation of data in a heterogeneous system environment consisting of a mainframe and distributed systems.
Migration: – Gradual migration of data and applications in heterogeneous system environments.
Modernisation: – Mainframe relief: Transfer of mainframe data to distributed systems or Hadoop Data Lakes.
Analytics & big data: – ETL of mainframe data for Data Warehousing, Business Intelligence, Analytics & big data.