Organizations are facing increasing pressure to reduce infrastructure costs, improve system performance, and prepare for modernization initiatives such as SAP S/4HANA, RISE with SAP, and Business AI. Yet many organizations still manage years, or even decades, of inactive data within their production systems, creating unnecessary complexity and expense. Meanwhile, SAP environments continue to grow.
Unmanaged data growth can lead to slower transaction processing, increased HANA memory consumption, longer backup and recovery windows, higher cloud and infrastructure costs, and greater migration risk. Left unaddressed, data volume challenges can significantly impact both operational efficiency and the success of future transformation initiatives.
SAP data archiving is one of the most effective ways to address these challenges. By systematically identifying and relocating inactive data, organizations can reduce database growth. It also optimizes system performance, supports compliance requirements, and establishes a stronger foundation for clean core and cloud strategies.
Today, archiving has evolved far beyond simply moving old records out of production systems. Successful initiatives require planning, governance, automation, and a long-term strategy. Below are eight best practices organizations should consider when building a sustainable SAP Data Volume Management (DVM) strategy.
The following best practices can help organizations build a long-term SAP data archiving strategy that delivers measurable business value while supporting ongoing SAP modernization efforts.
1. Start with a Data Volume Assessment
Before implementing any archiving initiative, organizations need visibility into what data exists, where growth is occurring, and which objects are driving database expansion. Without this understanding, archiving efforts often become reactive projects that fail to address long-term growth patterns. A Data Volume Assessment (DVA) helps organizations analyze:
- Database growth trends
- High-volume SAP tables
- Archivability opportunities
- Infrastructure impact
- Potential cost savings
- Retention and compliance considerations
A DVA establishes a roadmap for prioritizing archiving activities while helping estimate ROI, infrastructure savings, and performance improvements. This becomes especially important for organizations preparing for SAP S/4HANA migrations, RISE with SAP adoption, or broader clean core initiatives.
Rather than taking a one-size-fits-all approach, organizations can use the assessment findings to build a phased and strategic archiving plan aligned to business priorities.
2. Define Retention Policies Early
Effective archiving strategies must align with legal, financial, operational, tax, and regulatory requirements. One of the most common mistakes organizations make is archiving data without clearly defined retention policies.
Retention management defines:
- How long data should remain accessible
- When data can be archived
- When data may become eligible for destruction
Clearly defined retention policies help organizations maintain audit readiness, support legal hold requirements, meet industry compliance standards, reduce the risks associated with over-retention, and govern the complete lifecycle of enterprise data. By establishing and enforcing these policies, organizations can ensure that information remains accessible for business and regulatory purposes while minimizing unnecessary storage costs and compliance exposure.
Solutions such as SAP Information Lifecycle Management (SAP ILM) help enforce these policies throughout the full lifecycle of enterprise data, supporting compliance from creation through deletion.
An effective retention strategy should also distinguish between retention periods and residency periods. The retention period defines how long data must be preserved to satisfy legal, regulatory, tax, audit, or business requirements. The residency period determines how long data remains in the production system before it becomes eligible for archiving.
3. Select the Right Storage Strategy for Archived Data
Archiving data is only one part of the strategy. Organizations must also determine where archived data should reside. The right storage approach can significantly impact infrastructure costs, HANA memory consumption, accessibility, scalability, and compliance readiness.
Modern SAP archiving strategies commonly leverage SAP-certified storage solutions, hyperscaler environments like AWS, OpenText repositories, lower-cost archive storage tiers, and hybrid cloud architectures.
Another emerging option is DMS+ by Auritas, which enhances SAP BTP DMS capabilities for ADK file storage and AI-powered functionality.
As organizations move toward cloud-first SAP environments and RISE with SAP, storage optimization becomes increasingly important. The goal is to move inactive data away from expensive production infrastructure while maintaining secure and compliant access when required.
4. Automate Ongoing Archiving with Tools Like Data ASSIST
Many organizations perform a one-time archiving cleanup before a migration project and then stop. Over time, database growth resumes, system performance declines again, and infrastructure costs continue to increase. Long-term success requires continuous and automated archiving processes.
SAP data archiving automation solutions such as Data ASSIST by Auritas, help organizations automate and sustain archiving strategies by:
- Scheduling archiving jobs
- Monitoring archiving activity
- Maintaining ongoing database optimization
- Providing visibility into database growth trends
Automation helps organizations maintain a stable, controlled database footprint, preventing growth spikes after a project concludes. This reduces unexpected storage costs, licensing increases, and infrastructure expansion. No surprises when it comes to data growth and needs to increase storage size.
Automating the process also eliminates manual scheduling errors and improves consistency across archiving cycles. Organizations gain greater visibility into overall database health while proactively controlling growth rather than reacting to performance and cost issues after they arise.
TTI, Inc. faced growing database management challenges as its SAP environment expanded. To address rising infrastructure costs and performance concerns, SAP engaged Auritas to implement Data ASSIST, an SAP BTP-based solution that automates archiving activities and provides ongoing database optimization.
The project resulted in a 60% reduction in database size, significantly lowering hardware and hosting costs while improving database performance by 19%. TTI also gained seamless access to archived and active data for reporting purposes, helping improve compliance, operational efficiency, and long-term control over database growth.
5. Prioritize High-Impact Archiving Objects First
Not all SAP objects provide the same value when archived. Organizations should initially focus on high-growth transactional objects that contribute most heavily to database expansion and performance degradation. Prioritizing these areas helps generate faster ROI and measurable operational improvements early in the project lifecycle.
High-impact archiving candidates often include:
- Financial documents
- Material documents
- Sales orders
- Purchasing documents
- IDocs
- Workflow logs
- Spool data
- Industry-specific objects such as IS-U or PRA
By focusing on the largest contributors first, organizations can rapidly reduce database size, improve system performance, and simplify ongoing administration. A phased methodology also helps build internal momentum while generating measurable savings early in the initiative.
At the same time, organizations should not overlook compliance-driven objects. Some objects may deliver smaller database reductions but still play a critical role in meeting retention requirements, supporting audits, or serving as prerequisites for larger archiving activities. The most effective strategies balance storage optimization with governance and compliance needs.
6. Maintain Audit Readiness with SAP DaRT
Reducing database size should never compromise audit readiness or compliance accessibility. SAP DaRT (Data Retention Tool) enables organizations to extract and retain structured audit and tax data in compliant formats while reducing reliance on production systems for historical reporting.
Instead of maintaining years of inactive transactional records directly inside production systems, organizations can leverage DaRT to securely retain required audit information while still reducing database footprint. This is even more important for organizations in highly regulated industries like utilities, banking, health care and more.
7. Expand Beyond Archiving with Broader DVM Strategies
Data archiving is only one component of a broader Data Volume Management strategy. Organizations looking for long-term SAP optimization should also explore complementary approaches such as SAP HANA Native Storage Extension (NSE) and HANA memory optimization.
SAP HANA NSE allows organizations to move warm data outside expensive in-memory storage while still keeping it accessible when needed. This helps balance system performance with infrastructure cost optimization.
HANA memory optimization focuses on reducing the amount of active memory consumed by SAP systems through strategies such as database right-sizing, identifying unused or redundant data, optimizing table usage, improving data aging approaches, and reducing unnecessary memory-intensive workloads. These optimization efforts help organizations improve system performance while lowering HANA infrastructure and licensing costs.
Rather than relying on a single optimization method, organizations should combine multiple strategies to effectively manage long-term SAP growth, improve scalability, reduce HANA memory consumption, and optimize overall infrastructure utilization.
8. Connect Archiving to a Broader Data Management Strategy
The most successful organizations do not treat archiving as a standalone technical initiative. Instead, they integrate archiving into broader enterprise strategies such as clean core, data governance, content management, compliance management, and cloud transformation efforts.
This broader approach transforms archiving from a storage-reduction exercise into a long-term business enabler. Organizations with cleaner, governed, and optimized SAP landscapes are better positioned to support:
- Advanced analytics
- AI initiatives
- Automation strategies
- Faster cloud transformations
- Improved operational scalability
Organizations that implement structured archiving programs can achieve lower infrastructure costs, improved system performance, reduced memory consumption, faster migration timelines, stronger compliance management, and long-term database control. Long-term success requires more than simply moving old data out of production systems. It requires a comprehensive and sustainable data management strategy built for future growth.
Conclusion
As organizations pursue S/4HANA migrations, RISE initiatives, clean core objectives, and AI-driven innovation, controlling data growth becomes essential to reducing costs, improving performance, and minimizing complexity. By treating archiving as part of a broader enterprise data strategy, organizations can build cleaner, more efficient SAP environments that are better prepared for future transformation, innovation, and growth.
For organizations looking to get started, the first step is understanding the current state of their SAP landscape. A complimentary Data Volume Assessment (DVA) provides visibility into database growth trends, high-volume tables, and archiving opportunities across the environment.
The assessment helps organizations determine what data can be archived, what may be eligible for deletion, and what must remain accessible to satisfy business, compliance, and retention requirements. By establishing a clear baseline and roadmap, organizations can prioritize high-impact opportunities, quantify potential savings, and build a sustainable Data Volume Management strategy that delivers long-term value from their SAP investments.
Get started, get your complimentary data volume assessment now.
