Andrew MarshOver several years, a big financial institution ran everything on its most trusted mainframe system. It had powered countless transactions and audits. But all that valuable historical data lived in an expensive, overly complicated system that only a few experts could manage.
During a regular compliance review, regulators asked for ten years of transactional records. Simple enough, right? No, it wasn’t as simple as expected. What should have taken a few hours dragged on for days. The data was buried in unusual formats, and every query felt like decoding a mystery novel: expensive, stressful, and risky.
Meanwhile, the IT team was spending more time patching and monitoring the mainframe than driving potential projects. Licensing fees took up most of the budget. Even a small system enhancement could bring down the system operations. It felt like keeping a vintage car on the road when you can’t find the parts anymore.
The leadership team had enough. This wasn’t just about saving money; it was about regaining speed and control. They needed a way to keep all that historical data safe and accessible, without relying on the old technology.
The solution? What is smarter than Mainframe decommissioning with secure data archiving? In simple words, it means retiring the old system and moving all those records to a modern archive where they stay compliant, easy to search, and far less expensive to maintain.
Decommissioning their mainframe systems, migrating to more modern cloud-based alternatives and archiving historical data from their mainframe system deemed appropriate.
Mainframe system decommissioning is a coherent process of retiring a legacy mainframe system and migrating the data to a better alternative archiving platform. Following the mainframe decommissioning, the historical data is archived securely for long-term retention for compliance, analysis, and reference.
What’s Pushing Organizations to Retire Mainframe Systems?
Did you know that over 70% of enterprise data still sits on legacy mainframes?
High licensing costs, the skilled mainframe professionals gap, limited scalability, and security vulnerability are the paramount factors that drive mainframe decommissioning.
From the past, mainframe systems and technology were known for their reliability. Nevertheless, modern business demands cost-effectiveness and ease of maintenance, which makes legacy systems unsustainable for many organizations.
Let’s explore some scenarios that compelled the organizations to decommission or retire mainframe systems.
Industries Handling Big Data with Mainframe
Fintech industries like banks and insurance firms, having their core application running on Mainframe architecture for decades, face increasing challenges. The outdated programming languages and complex integrations become expensive to sustain. Also, with the shortage of talent in legacy technology, enterprises created a business case to modernize technology and their applications.
Imagine a global ecommerce platform that handles terabytes of transactional data within mainframe systems, requiring distributed storage systems like Hadoop or Cloud-based solutions. With traditional storage systems and databases, processing large volumes of transactional data turns out to be challenging.
Also managing data variety like structured and unstructured data, integrating into a single format is complex. The result? Messy data, inconsistent formats and skewed analytics.
Without rigid security and compliance, handling live and historical patient records on legacy mainframe systems can be a disaster for healthcare organizations. As data grows, data protection is not an option anymore. When it comes to sensitive information, following strict regulations like HIPAA, GDPR, or local laws is mandatory in any region.
Or look at the payroll data. Large scale payroll data comprising sensitive information, and personal data that requires regulatory compliance. Managing them on legacy mainframe systems turns out to be a nightmare, with scalability and security issues and no proper infrastructure for advanced analytics.
The truth is, tackling these challenges calls for more than just patching old systems. Then what do organizations require?
Organizations require a combination of robust technologies, distributed data storage, and governance frameworks aligned with organizational needs.
Mainframe Legacy System Incompatibility with Modern Software
IT organizations until the 90s, which kept their functionalities running live on Mainframe systems, faced issues such as lack of flexibility, no agility in existing applications, hassle in developing new mainframe applications, and mainframe skills.
In the present day, mainframe systems and applications combat integrate with modern cloud-based applications and APIs. The outcome? Extra operational complexity and performance setbacks.
Legacy mainframe architecture fails to adapt with modern DevOps and agile methodologies, making it difficult to respond to evolving market changes.
To make matters worse, old Mainframe Hardware and Software versions are no longer supported by vendors, creating business continuity risks.
Why Mainframe Decommissioning Matters?
Mainframe decommissioning is crucial, as maintaining age-old systems and redundant data is expensive and also vulnerable to potential threats.
Mainframes and IBM applications were once the backbone of enterprise computing. But times have changed. Today, most organizations are moving into the cloud because it’s more flexible, scalable, and cost-effective.
So, why is it so important to finally say goodbye to mainframes? Let’s walk through the reasons.
1. Expensive maintenance and hidden costs
Maintaining mainframe systems requires specialized hardware, unique software licenses, and experts who are rare to find (think COBOL programmers, who are getting harder to find). Large organizations like banks and insurance companies spend 75% of their IT budgets to keep their legacy systems functioning.
Considering the hidden costs, mainframe systems create technical debt. When developers are tried fixing and patching old mainframes, they’re not innovating, they’re stuck dealing with technical debt. Expenses on mainframe infrastructure maintenance could be alternatively spent on other potential initiatives.
Another big drawback? Mainframe systems keep their data siloed from modern analytics and data tools. Retiring these systems assists in interconnecting the data for references and detailed data inferences.
Considering the costs associated with mainframe hardware upgrades, software licensing, and skilled personnel, mainframes are expensive to operate and maintain.
Here is where the cloud flips the scenario. Migrating to cloud-based options gives more flexibility with pricing models, which can significantly reduce infrastructure and operational costs.
Modern cloud and distributed systems offer better speed and enhanced processing power for critical applications leaving legacy mainframe systems far behind.
2. Integration Hurdles and Siloed Data
Mainframe architecture is so outdated that it doesn’t support DevOps, microservices, and quick deployment. Their large, interconnected structure makes legacy applications slow and hard to update.
Ever thought of tedious integration? Integrating older mainframes with new cloud-based applications is challenging and doing this slows down system performance. This becomes a menace while organizations try to improve the user experience for their customers.
3. Security and Compliance Risks
Mainframe distributed systems lack the latest security updates and features, making them more vulnerable to cyber threats. Mainframe decommissioning and migrating to modern platforms enhances security with robust controls.
Let’s talk about another big problem, compliance. Ensuring legacy systems comply with changing data privacy regulations, such as GDPR, is a significant challenge. The decommissioning process helps consolidate data onto compliant platforms and apply data retention policies avoiding headaches.
And then there is a talent gap. As veteran mainframe developers retire, fewer experts are available to manage these systems. The failure to update and the knowledge gap can lead to project delays, making it more challenging to handle security problems as they arise.
4. Environmental Impact and Optimized resources
Legacy mainframe hardware and software usually consume more energy and take up more space than the latest cloud-based solutions. Organizations having their operations running through X86 hardware and IBM mainframe face increased power consumption. Additionally, the mainframe system’s dependence on data processing and larger storage contributes further to the climate crisis. This leads to a push to migrate to an advanced platform that could resolve the issue at a higher level.
By combining workloads, organizations can easily achieve their sustainability goals and operate far more efficiently.
What’s even better? When companies perform mainframe application decommissioning, they free up hardware and software, so the technical guys aren’t stuck handling the outdated hardware and software.
Also, read more about the challenges faced while modernizing the legacy application.
Key Stages in Mainframe Decommissioning
A lucrative decommissioning involves various stages of a methodical approach:
Discovery and Assessment
The comprehensive process starts with an audit to understand the mainframe architecture. This includes,
- Collecting a detailed inventory of mainframe applications, databases, and dependencies.
- Identifying critical processes and workflows.
- Segregating data to decide what needs to be archived, migrated, or removed.
Strategy and Planning
Hinged on the assessments, organizations build a modernization strategy and an extensive migration plan.
- Mainframe Rehosting – Migrating mainframe applications to a new platform with little or no changes to the code.
- Mainframe Re–platforming – Applying minor changes while moving applications to new platform, utilizing the cloud capabilities
- Mainframe Refactoring – Restructuring the mainframe application code to be native to the cloud and completely supports recent technologies.
- Mainframe Replacing – Swapping the legacy application with newer SaaS based options.
Data Migration and Archiving
Mainframe application redeployment journey starts with migrating data and application migration to the new platform.
Active operational data is moved to the new system, while historical data is archived for compliance and security.
New Platform Testing and Validation
The new platform is tested to ensure data integrity, functionality, and performance, to go beyond the old mainframe system capabilities. At this stage, both the old system and new platform operate simultaneously without interrupting the smooth transition.
Mainframe Shutdown and Hardware Disposal
After validating the new platforms, the entire mainframe system is powered down. The hardware is then securely removed and disposed of. For data security reasons, the old storage devices are completely wiped off or destroyed.
Why Mainframe Data Archiving Matters for Enterprises?
It is not about just storing old data. Archiving is much more. Archiving is about solving real challenges that enterprises face daily: increasing storage costs, compliance headaches, legacy system risk, and ensuring that valuable historical data is accessible long after systems are retired.
Here’s the reality: when organizations migrate off mainframe systems, they’re often left with decades of valuable data tied up in outdated applications. Think of COBOL-based billing systems, old DB2 applications, custom-built transaction engines, or reporting platforms that ran the business for years.
Mainframe Data Migration is about securely transferring decades of valuable information from outdated, costly legacy systems into modern, flexible platforms. Done right, migration ensures that structured, semi-structured, and unstructured data stays intact, compliant, and ready for use without disrupting business operations. With the right tools, data migration not only preserves historical records but also transforms them into assets that fuel business growth, compliance, and innovation for years to come.
So, what happens after you’ve migrated to a modern platform? Do you keep the legacy system running just for the data? That’s expensive, hard to secure, and tough to access. Delete the data? Not an option, you risk regulatory violations and legal exposure.
The smarter way?
- Migrate active data into the new system.
- Archive historical data from legacy mainframes into a secure, compliant archive.
- Decommission the legacy applications entirely
Mainframe data archiving isn’t just a cost-cutting tactic; it’s a business continuity and compliance responsibility.
Organizations modernize their mainframe data, whether by moving to cloud-native platforms, or on-premises storage. Modernization is not only about adopting what’s new, but also about managing what’s left behind.
Take the example of a financial services firm running a 25-year-old mainframe accounting system. The company switches to a modern SaaS ERP for real-time analytics and reporting. Perfect, right? Not quite.
That old system still holds decades of financial records, contracts, and audit logs. Regulators require them to be retained for 7–25 years, depending on the record type. Does it make sense to keep the legacy platform alive just to access these records? Absolutely, expensive and risky. Archiving that historical data into a modern, compliant solution is the only sustainable option.
Mergers, Acquisitions, and the Data Dilemma
If your enterprise has been through a merger or acquisition, you know what happens: duplicate records, siloed data, and redundant data everywhere. The fix? Archive the historical data from all legacy systems into a centralized, secure archive. Teams still get access to the records when needed, but the business can safely decommission redundant systems, reducing cost and risk.
The Explosion of Enterprise Data
IDC projects global data growth to hit 175 zettabytes by 2025, with structured data still representing a huge portion. Every transaction, audit log, customer record, and compliance report contributes to a huge pile of data.
The challenge?
- Rising costs of storing inactive data in outdated legacy systems
- Security and compliance risks tied to older technologies
- Operational inefficiencies caused by hanging onto systems that aren’t delivering business value anymore
Archiving solves this by moving inactive yet important data to a secure, optimized storage environment where it remains compliant, searchable, and accessible, without draining IT budgets.
Take your First Step Towards Smarter Modern Archiving
Why Choose Archon Suite – Your Full Stack Data Archiver
Meet Archon Suite, a comprehensive set of data tools built for data archival, safe migration, and management. With Archon Suite, your data migration and archival process becomes secure, compliant, and surprisingly smooth. Archon Suite incorporates Archon Data Store, Archon ETL, and Archon Analyzer to expedite mainframe data processing.
Mainframe Data archival and migration provides secure, accessible, and compliant long-term storage for structured and unstructured data.
Here is how it comes as a pack:
- Archon Analyzer helps ensure data integrity and provides insights into legacy mainframe data that help data migration and archiving strategies.
- Archon ETL handles the complexities of mainframe data extraction, transformation, and loading, while preserving the integrity of the structured data from the live systems.
- Archon Data Store (ADS) is a secure and compliant data Lakehouse optimized for mainframe data archival. ADS supports intelligent storage tiering (hot, warm, and cold) to make it cost-effective and improve live system performance.
Archon Analyzer for Mainframe Decommissioning
Migrating decades’ worth of mainframe data can be intimidating, but not with Archon Analyzer. When it comes to mainframe data migration, Archon Analyzer makes sure nothing hinders its path. It digs into your systems, breaks the complexity, and sets you up for a smooth migration journey.
Archon Analyzer is best at:
Analyzing Data Volume and Structure – Archon Analyzer breaks huge and complex data of various file types (VSAM, flat files, DB2, etc.), data formats, table layouts, and aged data. You get a clear data structure, no matter how big the data is.
Identifying Sensitive Data – Manually tagging sensitive fields is slow and error-prone. Archon Analyzer automates this process, dynamically flagging critical information to keep your compliance team safe.
Flagging Redundant and Duplicate Data – Why waste storage and money on duplicates? Analyzer detects unused and duplicate records, captures them, frees up space and eases smooth migration.
Retention Policy and Compliance Check – It compares the data with the latest data retention policies, flags and deleted unsafe data and retains what needs to be stored.
Don’t Let Legacy Systems Hold Back Your Growth
Archon ETL for Mainframe Decommissioning and Migration
Once Analyzer maps out the data landscape and identifies what needs to be archived, Archon ETL takes over. Archon ETL acts as a connector, securely migrating your classified data from aging mainframe systems.
Here’s how Archon ETL handles it:
Secure Extraction from Mainframe – Archon ETL extracts the critical information buried in mainframes, billing platforms or even old audit logs, no matter how outdated it is.
Metadata preservation – ETL ensures every piece of metadata such as timestamps, system origins, and user interactions are preserved during migration without breaking the thread.
Smart Transformation and Mapping – Legacy formats are not an issue anymore. Achon ETL transforms and maps your data to modern standards, ensuring it’s consistent, searchable, and usable in the new environment.
Data Cleaning for Compliance – Before archiving ETL cleans up outdated entries, duplicate records, and inconsistent formats to keep the new platform hold accurate and high-quality data
Teaming up Analyzer with ETL, mainframe decommissioning becomes less of a headache and more of a strategic move.
What else can Archon Suite for Mainframe Data Migration?
Archon Suite goes beyond “just moving your data”.
- Ensures that regulatory-compliant data is precisely maintained throughout the relocation process.
- Preserves referential integrity, metadata, and schema from source to archive.
- Transfers mainframe data to on-prem, cloud-based, or hybrid archives with ease.
Mainframe Data Archival Process with ADS
Archon suite provides a comprehensive, secure, and compliant approach to archive data from legacy mainframe systems. It ensures that historical data is accessible and audit-ready without relying on expensive mainframe architecture.
Archival Storage – Storing Archived data in a secure and searchable archive. Archived data is locked down as read-only to preserve integrity and avoid data breach or tampering.
Access control – Implementing smart data indexing and role-based access ensures the right people access the right data.
Compliant-ready – Automatically meets the long-term storage and audit requirements of the archived data.
Retention management – Applying automated policy enforcement for data lifecycle management.
Why Organizations Love Archon Data Store?
Archon Data Store enables smart mainframe data classification with detailed metadata mapping. The archived mainframe data is compliant and classified based on value, sensitivity, and legal requirements.
- Classifies data by value, sensitivity, and legal requirements.
- Enables quick search and seamless retrieval of archived mainframe data.
- Lowers the cost of archival storage by eliminating redundant information.
- Fuels data governance through accurate classification and enriching metadata.
- Instantly moves the data to the appropriate tier as it ages or loses relevancy.
- Maintains live data in performance-optimized tiers for speedier access.
- Change storage tiers instantly when data ages or becomes less relevant.
- Records deletion logs to provide legal defensibility.
- Reduces exposure to legal and regulatory risks.
How can your mainframe system data be securely decommissioned and archived? Our experts can guide you, talk to them.
Frequently Asked Questions
A seasoned IT leader with 20+ years of experience across legacy systems and modern enterprise technologies. Specializes in digital transformation, cloud architecture, and enterprise content strategy, with a proven track record of building high-performing teams and long-term customer partnerships.
