deBCor Engineering

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Optimize · Performance Optimization

Your SAP system should be faster today than the day it went live.

Most aren't. Custom code accumulates. Data volumes shift. Query patterns evolve. Indexes tuned in 2018 no longer fit today's workloads. Our engineers find the real bottlenecks and fix them at the root.

SAP Gold Partner#5 in USA · SAP PartnerFinderExpert BDC · BTP · Business TransformationSenior-Led, Global Delivery

SAP Partner Ranking

#5 in the USA

Founded

1997 · 29 Years

Partner Tier

Gold · Expert BTP, BDC & Business Transformation

Delivery Model

Senior-Led, Global Delivery

Certifications

Every SAP Architect Tier

The Problem

Slow systems cost more than you think.

SAP systems that started fast eventually slow down — not because they were built badly, but because nothing stands still. Data volumes grow. Custom Z-code accumulates. Batch windows tighten. Indexes tuned in 2018 no longer fit today's query patterns. By the time users complain, the system has usually been degrading for months.

And the bottleneck almost never lives where the steering committee thinks it does.

01ABAP

Custom code debt

Every Z-program written to compensate for a limitation has a cost. When enough of them accumulate, simple transactions drag — even on modern HANA hardware.

02HANA

Data volume & schema drift

Table growth, inefficient indexes, partitioning decisions that made sense at go-live — these compound quietly over years until the pain becomes undeniable. And database size itself becomes a cost and performance liability when attachments and documents accumulate unchecked.

03Batch

Batch window collapse

Batch jobs that once ran in two hours now take eight. Not because of more data, but because nobody's looked at the scheduling logic, parallelization, or dependencies in years.

04Integration

Integration overhead

Synchronous middleware calls, polling-based integrations, and inefficient IDoc processing patterns impose hidden latency on every business transaction.

How We Deliver

Four steps. Real fixes.

Structured remediation built around business impact — not a list of recommendations you implement yourself.

01

Measure, don't guess

We instrument the actual system — not the PowerPoint version of it. Runtime Analysis, SQL Trace, HANA Plan Visualizer, ABAP Trace, Code Inspector, and ATC give us the real picture, not the one your steering committee has been working from for six months. The actual bottleneck almost never lives where the rumor says it does.

SAT / Runtime AnalysisSQL Trace (ST05)HANA Plan VisualizerCode Inspector / ATCABAP Profiler
02

Triage by dollars

Revenue-blocking transactions go first. Batch windows second. Reports last. We surface quick wins immediately — something improves this week — while the deeper structural work runs in parallel. Every remediation item is mapped to a business outcome, not just a technical metric.

03

Remediate at every layer

Root causes fixed — not symptoms managed. Code refactoring, index and partitioning strategy, parallel batch design, column-store tuning, archiving and data tiering, CDS view redesign. The Z-table dragging order entry gets a real architectural fix, not a faster server underneath it.

ABAP RefactoringIndex & Partitioning StrategyParallel Batch DesignColumn-Store TuningData ArchivingCDS View Redesign
04

Leave monitoring behind

Permanent dashboards and alerting so your team catches regressions before users do. Optional rollover into Managed Services for ongoing stewardship. Performance is not a project — it's a habit. We make sure the habits are in place before we leave.

HANA Monitoring DashboardsDVM / Workload MonitorManaged Services Integration

The AI Difference

Experience plus AI. Neither is sufficient alone.

Decades of SAP performance work taught us where to look. Our AI tooling now dramatically accelerates how fast we get there — and exposes patterns no manual review would catch at scale.

AI-Accelerated Code Analysis

Our AI tooling scans entire custom code landscapes in hours — identifying performance anti-patterns, SELECT * statements, nested loops on large datasets, and missing index keys across thousands of programs simultaneously. What once took weeks of manual review now surfaces in a single sprint.

Pattern Recognition Across Landscapes

DEBCOR's delivery library — built from 29 years of SAP engagements — is encoded into our AI toolset. When we see a degraded HANA workload class, our tools cross-reference known root-cause patterns from similar landscapes to narrow the diagnostic field before the first trace runs.

AI-Assisted Remediation Planning

After diagnosis, our AI tooling generates prioritized remediation plans with effort estimates, risk classifications, and business impact projections — enabling faster executive buy-in and more predictable delivery timelines.

Continuous Regression Detection

Post-optimization, AI-powered monitoring agents watch workload patterns and surface emerging regressions before they reach end users — turning one-time performance projects into continuous improvement programs.

Our engineers bring deep, hands-on SAP performance experience — augmented by DEBCOR's AI tooling and 29 years of client delivery patterns — to every engagement.

Hidden Weight

Your database is probably bigger — and slower — than it needs to be.

Most SAP clients focus performance work on code and queries. Fewer look at what the database is actually storing. After years of operation, the majority of SAP database growth isn't transactional data — it's attachments. Purchase order PDFs. Invoice scans. HR documents. Inspection photos. Quality certificates. GOS-linked files accumulated across every module, silently inflating the footprint of a system that was never designed to be a document repository.

The result: longer backup windows, slower restores, higher licensing exposure, higher hyperscaler storage costs, and HANA in-memory pressure from tables that should never have grown this large.

The fix is architectural, not just a cleanup sprint.

What's driving the bloat

SAP's Generic Object Services (GOS) framework makes it trivially easy to attach files to any business object. That convenience has a long-term cost: every attachment lives in the database, often in BLOB columns, growing the physical footprint of tables like SOFFCONT1, SOFFPHIO, and SOOD — none of which benefit from HANA's columnar compression.

A mature SAP landscape running since the mid-2000s may have accumulated tens or hundreds of gigabytes — sometimes terabytes — of attachment data that could be offloaded to object storage at a fraction of the cost, without any loss of user-facing functionality.

  • SOFFCONT1 / GOS attachment tables growing unbounded
  • Backup and restore windows extending due to attachment volume
  • HANA memory pressure from oversized row-store tables
  • Storage costs scaling with transactional volume
  • Disaster recovery complexity increasing with database size
DEBCOR Product

Attachment Offload to Hyperscaler Storage

DEBCOR's GOS/Azure Blob solution moves existing attachments — and all future attachments — out of the SAP database and onto Azure Blob Storage (or AWS S3, Google Cloud Storage). The links back to every purchase order, invoice, HR record, and quality document are fully preserved. Users experience no change in how they access documents. The database loses the weight.

This is not archiving in the traditional sense — documents remain instantly accessible via the same GOS attachment viewer users already know. They simply no longer live inside SAP.

Learn more about attachment offload →
Engineering

SAP Data Archiving & ILM

For transactional data that genuinely needs to leave the database — completed sales orders, historical invoices, aged HR records — DEBCOR designs and builds SAP Data Archiving programs using SAP's native Archive Development Kit (ADK) and Information Lifecycle Management (ILM) framework. Data moves to near-line storage or cold tiers, remains accessible for reporting and legal hold, and stops consuming active HANA resources.

Recommended Approach

Attachment Offload + Archiving Together

The most impactful database reduction programs combine both: attachments offloaded to hyperscaler object storage (immediate, low-risk, high-volume reduction) and transactional archiving for aged business data (deeper, longer program, compliance-aligned). Together, these can reduce active database footprint by 40–70% in mature landscapes — with measurable impact on backup windows, HANA memory, and storage costs.

Clients who combine attachment offload with transactional archiving typically see:

  • 40–70% reduction in active database footprint
  • Backup window reductions of 30–50%
  • Storage cost reductions of 60–80% on attachment data (hyperscaler vs. SAN/block storage)
  • All document links preserved — zero user workflow disruption

Why deBCor

Credentials that matter here.

Performance optimization is a senior discipline — it can't be reduced to canned scripts. Senior architects lead every diagnosis, and our team's depth is what separates a permanent fix from a temporary workaround.

Deep Performance Pedigree

Engineers with hands-on experience diagnosing the most complex performance crises in global enterprise SAP landscapes.

HANA Internals Expertise

Firsthand knowledge of how HANA's workload management, optimizer statistics, and column-store engine behave under production load.

29-Year ABAP Pedigree

Gareth de Bruyn co-authored the first ABAP book ever published (1996) and holds one of the original SAP technical certifications in the world. Our ABAP refactoring is the real thing.

Every SAP Architect Certification

Our Chief Architect holds every SAP architect-tier certification SAP offers — P_SAPEA, plus the full suite of functional and technical domains.

DEBCOR AI Toolset

Proprietary AI-powered tooling for code analysis, pattern recognition, and regression detection — purpose-built for SAP performance engagements.

Cross-Industry Library

Performance patterns documented across pharma, life sciences, defense, manufacturing, energy, retail, insurance, and financial services — so your engagement benefits from every prior one.

“deBCor's white-glove approach to consulting isn't just a tagline — it's the reality of their service. They've been our trusted partner for many years. At our request, they cleaned up our technical debt and prepared us for S/4HANA. The migration only took four months — we were down for maybe a weekend, then back to business with no loss in revenue.”

Travis Call · CIO, iFIT

FAQ

Common questions.

How do I know if I need performance optimization?

If users are experiencing delays, complaints cluster around specific transactions, or batch windows are overrunning — it's worth a diagnostic. But even healthy-feeling systems degrade silently. We often find performance has been declining for 12–18 months before anyone identifies it as systemic rather than individual.

Do you work on ECC, or only S/4HANA?

Both. ECC on AnyDB, ECC on HANA, S/4HANA on-premises, S/4HANA Cloud. The toolsets and remediation patterns differ, but the diagnostic discipline is the same. If you're on ECC and approaching end-of-support, we can structure the engagement to clean technical debt as a migration-preparation activity — one investment, two outcomes.

What does HANA-specific tuning look like?

Column-store optimization, partitioning strategy, delta-merge tuning, optimizer statistics, workload class management, and CDS view design — both at the database layer and at the application layer that accesses it. HANA performance is often misunderstood as a DBA problem; the biggest wins usually come from how the ABAP application interacts with the in-memory engine, not from the engine itself.

How long does a typical engagement take?

Diagnostic phase is typically 2–4 weeks. Remediation scope depends on findings — from a few weeks for targeted hotspot fixes to a multi-quarter program for a full custom-code overhaul. We provide a prioritized remediation backlog at the end of diagnostics, so you can make an informed scope decision before committing to remediation.

My database has grown enormous. Is that a performance issue?

Yes — and it's one of the most underdiagnosed ones. In mature SAP landscapes, database size is often dominated by attachment data (GOS objects, scanned documents, IDoc archives) rather than transactional records. This drives longer backup windows, higher storage costs, and HANA memory pressure. DEBCOR offers two complementary approaches: attachment offload to hyperscaler storage (Azure Blob, AWS S3, or GCS) with all document links preserved, and SAP data archiving for transactional records using SAP's native ADK/ILM framework. Most clients see 40–70% database footprint reduction when both are applied together.

Can this roll into Managed Services?

Yes, and it's often the right structure. Performance optimization that doesn't leave ongoing monitoring in place tends to regress. Rolling into Managed Services means the dashboards, alerting thresholds, and institutional knowledge we built during optimization stay active — and emerging issues are caught before they become user complaints.

What industries do you serve?

Our performance work spans pharma, life sciences, defense, manufacturing, energy, retail, insurance, financial services, and technology. Diagnostic patterns are largely universal — but remediation priorities, data-archiving considerations, and compliance constraints vary by industry. Our cross-industry library means we're not learning your industry during your engagement.

Ready to go further after optimization?

See AMS / Managed Services

Approaching the 2027 ECC deadline?

See RISE with SAP

Want to understand our AI tooling?

Explore our AI practice

Ready to find the real bottleneck?

Start with a conversation. We'll tell you what's actually going on in your landscape — and what fixing it is worth.