In this fact sheet, you will learn how the CONNX for VSAM module provides secure, real-time and read/write access to VSAM™&nbsp; data sources on MVS™, z-OS®&nbsp; and z/VSE®. With other modules, seamless performance is what you’ll expect with support for VSAM/CICS® on OS/390®/z/OS CONNX for VSAM. Additionally, it runs as a CICS transaction, ensuring interoperability with existing CICS applications.<br> <br> The benefits don’t stop there as the CONNX for VSAM module operates well with other CONNX suite products, performing seamless joins between two or more supported disparate databases with ODBC, OLE DB, JDBC and .NET. With speed and efficiency, all you’ll need is a single metadata model created to span the entire enterprise data source portfolio and all applications requiring data access.<br> <br> The result? An enterprise-wide view of your data, providing a reusable standards-based framework for information access. Get all the technical details on how this is possible with the CONNX for VSAM module for data integration in this fact sheet.

See how to synchronize all your data sources to the cloud with one tool, CONNX Data Replication for Snowflake.

Strategically, companies can't deny the advantage data integration brings to the table, driving new business and digital transformation initiatives toward a new competitive differentiator. This is at the forefront for CONNX with results in comprehensive data integration capability across all distributed and heterogeneous data landscapes.<br> <br> Additionally, unique capabilities CONNX provides are speed and security . CONNX accomplishes this via connectivity within a diverse spectrum of databases not limited to legacy, relational, big data and cloud. Seamless integration is a snap on mainframes, HP®&nbsp; OpenVMS, iSeries (AS/400), UNIX®, Linux®&nbsp; and Windows®. Other features include data access, virtualization, movement, migration and replication in one integrated environment.<br> <br> See how CONNX provides those rapid results with comprehensive data integration capabilities across distributed and heterogeneous data landscapes.