App Store Economics for Mainframe Integration Software

What if enterprise integration software were priced like a smartphone app store — pick the specific capabilities you need and skip the ones you don't? VirtualZ Computing CTO Vince Re explains how VirtualZ applies that model to mainframe integration, letting enterprises choose individual connectors and capabilities instead of buying a large suite and using a fraction of it. Vince Re contrasts the traditional "buy everything, use some of it" enterprise software model with a modular, app-store approach: granular selection, pay for what you use, and combine specialized components into exactly the integration you need. He explains why modular architecture also lets a vendor ship new capabilities faster than monolithic, all-in-one development. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How app-store-style pricing changes enterprise software buying — paying for a handful of capabilities instead of dozens - Examples of modular components working together, such as the Splunk connector, the data-movement multiplexer, and cloud storage - Why modular architecture accelerates innovation compared with monolithic platforms - The advantages of granular selection: lower cost, faster implementation, and flexibility to change later - How customers assemble custom mainframe integration by combining specialized capabilities This modular philosophy runs through VirtualZ Computing's no-code portfolio for enterprise mainframe data: PropelZ (moving and replicating IBM Z data to the cloud, proven at 56,000 records per second), Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage) — four products you deploy and combine, with no code and no homegrown pipelines, rather than one suite you buy whole. Topics: enterprise software pricing, modular architecture, mainframe integration, IBM Z, z/OS, connectors, no-code data integration, software procurement, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/