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X-WR-CALDESC:No-code IBM Z data integration, live data access, cloud file storage, and z/OS storage modernization for AI, analytics, and enterprise applications.
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SUMMARY:How to Get VSAM and Mainframe Data into Databricks — Without the Staging Hops: Native Databricks Delivery with PropelZ
DESCRIPTION:“Just stage it first.”\nThat’s the reflex the moment anyone wants mainframe data in Databricks. Unload it to a flat file. Move it off the mainframe. Land it in object storage. Decode it, convert it, and only then load it. Every one of those hops is something to build, something to secure and something to keep running — and every hop adds hours between the system of record and the business teams waiting on the data.\nNot because the data is hard to reach; the mainframe is right there. It’s because most mainframe data-sharing tools were built in the ’80s and ’90s, for the ’80s and ’90s — when mainframes couldn’t talk to other platforms directly, so data was copied to a middle tier and read and written again on its way out. Add EBCDIC text, packed decimal, floating point and records with a thousand fields, and every new target becomes a project for scarce, highly skilled people. Every layout change means doing it again. The result is IT backlogs measured in years — and business units told to go find their own solution.\nIn this recorded session, VirtualZ Computing founder and CEO Jeanne Glass and co-founder and CTO Vince Re show what data access built today, for today, looks like. PropelZ, VirtualZ’s patented data access software, runs where the data lives and goes from the mainframe straight to the target — no middle tier, reading the data once and writing it once. For Databricks, a native driver bulk-loads data in large single transactions instead of row-by-row JDBC inserts. There is no code to write: point PropelZ at your data and the COBOL copybooks you already have. And with 90 to 95 percent of its processing landing on zIIP engines, it won’t drive up your MIPS bill.\nLegacy tools and PropelZ both move data, the way a wall phone and a smartphone both make calls. If your path to Databricks still runs through several staging stops, this session shows you the direct route.\nWhat is PropelZ?\nPropelZ is VirtualZ Computing’s patented, no-code data access software for moving mainframe data to any target. It reads VSAM, sequential files, tapes, GDGs, databases and network file shares; transforms records using the COBOL copybooks you already have; and writes directly — with no middle tier — to more than 100 JDBC databases, cloud object storage, file shares, APIs and Databricks, through a native Databricks driver built for bulk loading. Credentials stay in RACF, ACF2 or Top Secret, and 90 to 95 percent of its processing is zIIP-eligible.\nWhat you’ll see\n\nWhy legacy mainframe data pipelines have so many hops: architectures built for the ’80s and ’90s, a middle tier that reads and writes the data again, hexadecimal dumps, scarce skills and rework every time a layout changes\nHow PropelZ is architected differently — an input stage, a transformation core and an output stage that runs where the data lives and goes straight to the target, reading the data once and writing it once\nThe native Databricks driver: bulk-loading 100,000 rows in a single transaction instead of row-by-row JDBC inserts, for roughly a sixfold improvement — and reading Databricks data back out through certified JDBC connectivity\nNo-code transformation from existing COBOL copybooks: EBCDIC, packed decimal and floating point handled automatically, with column selection and record filtering on the way through\nSecurity and cost: the encryption and authentication your target supports, credentials kept in RACF, ACF2 or Top Secret, hardware crypto, and 90 to 95 percent zIIP eligibility\nInstall and operate at scale: an archive restored into z/OS UNIX with no prerequisites, runs triggered from the command line, your scheduler, OPS/MVS or a batch job step, and a massively parallel option for tens of thousands of files — plus how an ISV cut customer data-feed processing from eight hours to one to two\n\nWho should attend\nDatabricks platform owners and data engineering leads; mainframe architects, systems programmers and IT operations teams; enterprise data platform owners and integration leads; analytics, AI and ML owners; ISVs that ingest customer data feeds; and CIOs and chief data officers responsible for getting mainframe data into Databricks — anyone who maintains, or is about to build, a multi-stage pipeline between z/OS and the lakehouse and would rather not.\nHosts\nJeanne Glass, Founder and CEO, VirtualZ Computing · Vince Re, Co-Founder and Chief Technology Officer, VirtualZ Computing\nIn a partner’s words\n“With PropelZ, we can move usable, decoded copies directly so our teams can perform reconciliation and analytics. That removes several stages from the pipeline and gives us a more direct path from core data to operational insight.”\n— Shahir Daya, Chief Product & Technology Officer, Zafin\nWatch now →\n\nGetting VSAM and mainframe data into Databricks with PropelZ\nQ. What does PropelZ do for Databricks?\nA. PropelZ moves mainframe data into Databricks directly, with no staging hops. It reads VSAM, sequential and other mainframe data at the source, transforms it using existing COBOL copybooks, and writes it to Databricks through a native driver that bulk-loads data in large single transactions. PropelZ can also read data back out of Databricks through certified JDBC connectivity.\nQ. How do you get VSAM data into Databricks?\nA. The traditional way is a multi-step pipeline: unload VSAM to a flat file, move it off the mainframe, land it in object storage, decode and convert it, then load it. With PropelZ, VSAM data is read once on the mainframe, transformed in flight and written straight into Databricks, with no code and no intermediate platform.\nQ. Why do mainframe-to-Databricks pipelines have so many hops?\nA. Most mainframe data-sharing tools were designed in the ’80s and ’90s, when mainframes couldn’t connect directly to other platforms. They copy data to a middle tier, which reads it and writes it again before it reaches the target. Each pass adds latency, cost, something to secure and something that can break. PropelZ removes the middle tier and goes from the mainframe to the target directly.\nQ. Why is PropelZ faster loading Databricks than standard JDBC?\nA. Databricks’ standard JDBC interface isn’t built for bulk inserts, so writing row by row is slow. PropelZ uses a native Databricks driver that loads data in bulk — for example, 100,000 rows in a single transaction — which delivers roughly a sixfold improvement. More broadly, PropelZ optimizes for each target’s most efficient load method.\nQ. Do I need to write code or decode mainframe records by hand?\nA. No. PropelZ is no-code. You provide the data and the metadata you already have, typically COBOL copybooks, and PropelZ handles EBCDIC text, packed decimal and floating-point formats. You can select only the columns you need and filter records. For database sources, the metadata comes from the database itself.\nQ. How much faster is PropelZ than legacy approaches?\nA. Customers typically see PropelZ run at least twice as fast as legacy approaches, and often far faster. Because PropelZ reads the data once and writes it once, jobs that ran from Friday afternoon into Monday have finished in a couple of hours, and three-day runs have dropped to two hours.\nQ. Is mainframe data secure when PropelZ moves it to Databricks?\nA. Yes. PropelZ supports the security your target supports, including TLS encryption in flight and Databricks’ authentication methods. Credentials can be stored and managed in RACF, ACF2 or Top Secret, and PropelZ can use the mainframe’s hardware crypto. There is no intermediate Windows or Linux server holding credentials.\nQ. Does PropelZ raise the mainframe MIPS bill?\nA. No. Typically 90 to 95 percent of the processing PropelZ uses lands on zIIP specialty engines, so moving large volumes of data doesn’t require more mainframe capacity or drive up software costs.\nQ. Can PropelZ handle thousands of files at once?\nA. Yes. PropelZ includes a massively parallel option: you give it an inventory of files and a limit — 10, 100 or 1,000 at a time — and it orchestrates and monitors the runs, so failures are easy to find and rerun. Customers use it for tens of thousands of files and for tape libraries with up to a million data sets.\nQ. How long does it take to install PropelZ and load Databricks?\nA. PropelZ ships as an archive that you restore into a z/OS UNIX directory, with no prerequisites, no system changes and no special privileges. It installs in minutes and configures in hours, and customers are typically testing the same day. The main work is connectivity — Databricks credentials, certificates and firewall ports — and most teams prove it out within a week.\n
URL:https://virtualzcomputing.com/events/vsam-mainframe-data-databricks-propelz-webinar/
CATEGORIES:Featured Col 1,Upcoming
LOCATION:Virtual
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