ArcXA IBM Power Schema-Mapping Service

 

ArcXA IBM Power

Schema-Mapping Service

Equitus.ai  ·  ArcXA  ·  May 2026

"ArcXA removes migration bottlenecks with an Intelligence Context Layer"

ArcXA introduces an intelligent context layer and robust data governance to bridge the gap between separate infrastructure silos. Enterprise transformation initiatives — such as migrating core databases from Oracle to IBM SAP/Rise — face organizational misalignment, data evolution tracking challenges, and governed data movement bottlenecks.

ArcXA (an open-source semantic mapping and data migration platform by Equitus.ai), paired with Knowledge Graph Neural Networks (KGNNs), provides a technical architecture to solve these problems.

It can be systematically applied to assist IBM groups using P11 methodology across:

•     Passport Advantage

•     Lab Services

•     Tech Life Services (TLS)

1. ArcXA — Addresses Misalignment, Evaluation Sets, and Data Selectors

ARCXA resolves friction between business definitions (the semantic layer) and technical realities (physical database tables) through data-centric governance.

Organizational Misalignment

Misalignment typically occurs because database administrators, ERP functional consultants, and risk/compliance officers speak different technical languages and pursue different goals.

The ArcXA Solution: ArcXA implements an ontology-aware semantic mapping engine. Rather than mapping columns directly from Oracle to SAP HANA, it maps Oracle source schemas to a unified ontology (business concept layer), which then maps cleanly into SAP/Rise schemas. This creates a single source of truth where stakeholders align on business logic, not raw SQL.

Evaluation Sets

During migration, validating that data has not been corrupted or misaligned is essential.

ArcXA Solution: ArcXA abstracts complex migrations into repeatable workflows with integrated

System-of-Systems (SoS) validation. It materializes and freezes specific snapshot evaluation sets (managed datasets), enabling validation teams to test target-side transformation outcomes against baseline policies before executing production cutovers.

Data Selectors and Intelligent Analytics

Moving massive legacy Oracle footprints into SAP/Rise requires migrating only what is necessary.

ArcXA Solution: ArcXA utilizes intelligent analytics via its model-assisted inference service

(arcxa-model-service). Using embedding models, it suggests relevant data selectors — identifying which legacy tables, rows, or historical segments match specific SAP modules (Finance, Supply Chain, etc.). Combined with KGNNs, the system builds an entity graph of database relationships, alerting architects to downstream impacts when certain data selectors are excluded.

2. Use Case: Oracle to IBM SAP/Rise Migration

Migrating off Oracle to RISE with SAP on IBM Power Virtual Server involves heavy database refactoring — converting to SAP HANA or AnyDB. ArcXA accelerates this lifecycle in three phases:

[Oracle DB Schema] ■■> [ARCXA Semantic Mapping Engine] ■■> [SAP S/4HANA (RISE)]

                             ■ (Graph Lineage & KGNNs)

                    [Governance Context Layer]

Schema Evolution & Traceability

ArcXA doesn't just pipe data — its graph-native RDF engine (arcxa-shard) maps row, column, and schema evolution. If an Oracle stored procedure relies on a specific data hierarchy, ArcXA highlights the transformation lineage so developers know exactly how it translates to the target SAP environment.

Semantic Normalization

ArcXA auto-aligns Oracle-native fields with SAP S/4HANA's standardized global ontologies via R2RML (W3C standard mapping), ensuring structural and semantic consistency.

Automated Data Validation

Dry-runs and automated approval gates ensure that when data lands in the SAP/Rise environment, it complies with pre-set security and organizational governance rules.

3. Deployment via IBM Services Groups (Leveraging P11 & KGNNs)

IBM can deploy ArcXA and KGNN capabilities across its major commercial and technical delivery frameworks — guided by P11 programmatic governance models (standard phased migration playbooks or classification standards).

A. Passport Advantage

Role: Soft licensing, procurement, and software lifecycle optimization.

ArcXA Integration: Passport Advantage teams can use ArcXA's cataloging views and managed dataset profiles to inventory existing database footprint entitlements. By adding a KGNN context layer to a client's software asset registry, IBM can visualize how Oracle workloads map to IBM Db2 or SAP/Rise cloud options — identifying cost optimizations and proving TCO reduction prior to migration.

B. Lab Services

Role: Deep-dive technical product implementation, architecture design, and first-of-a-kind engineering.

ArcXA Integration: Lab Services engineers can deploy arcxa-coordinator and arcxa-shard (the RDF/SPARQL graph data plane) directly into client sandbox environments. Using KGNNs, Lab Services can train graph networks on historical migration patterns. The network learns how custom Oracle schemas typically map to SAP tables, automating 70–80% of legacy schema conversion tasks.

C. Technology Lifecycle Services

Role: Long-term infrastructure optimization, performance tuning, and lifecycle maintenance for IBM Power VS hosting SAP workloads.

ArcXA Integration: Post-migration, TLS can maintain ArcXA as a persistent governance context layer. As business needs evolve under a P11 operational model, TLS uses the platform's active lineage graph to trace data compliance, monitor policy-driven validation drift, and ensure operational databases running under RISE with SAP remain optimized and aligned with enterprise governance models.

Published May 19, 2026  ·  arcxa.blogspot.com  ·  equitus.ai

ArcXA is an open-source semantic mapping and data migration platform by Equitus.ai. KGNN, EVS, ARCXA, and related marks are property of Equitus Corporation.

ArcXA intelligence layer: IBM-centric enterprise environment

IBM-centric Enterprise Environment

"Complex, cross-platform migrations (like moving from Oracle to SAP and Db2) cause traditional data structures to fail." 

Power your Migration with ArcXA, built on Equitus.ai -Triple Store Architecture which powers the semantic intelligence layer automating ETL.

Traditional databases use rigid tables, rows, and columns. ArcXA, however, uses a Triple Store to model your entire data ecosystem as a Knowledge Graph.

Every piece of information is stored as a "triple": [Subject --->Predicate ---> Object].

• Example: [Table_A] — (contains_sensitive_data) —> [True]

• Example: [Oracle_Column_X] — (maps_to) —> [SAP_Field_Y]

ArcXA Architectural choice directly accelerates and enables the capabilities across your three diagrams:

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1. The Pipeline View (Semantic Alignment)

Moving data from Oracle to SAP and IBM Db2 isn't just a plumbing problem; it’s a translation problem. Oracle, SAP, and Db2 all speak different data dialects and structural languages.

• What the Triple Store does: It acts as a universal semantic bridge in the middle (ArcXA). Instead of writing hardcoded, brittle mapping rules from Oracle to SAP and separate ones from Oracle to Db2, the Triple Store maps Oracle's metadata into a generalized semantic model.

• The Acceleration: Because the relationships are stored as independent facts (triples), ArcXA can automatically infer how an Oracle data structure should look in SAP or Db2 without manual schema mapping. If a change happens in the Oracle source, the graph updates the relationship dynamically, preventing pipeline breakage.

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2. The Three Capability Pillars (The Intelligence Engine)

Triple Store is the underlying engine that makes the three pillars highly automated rather than human-labor-intensive.

       [ Triple Store Knowledge Graph ]
         /            |             \
        v             v              v
[ Pillar 1: ETL ] [ Pillar 2: Data ] [ Pillar 3: Eval ]
[ Cost Reduction] [   Selectors    ] [ Set Generation ]

Pillar 1: ETL Cost Reduction

• Problem: Traditional ETL analysis requires data analysts to manually trace code, documentation, and database schemas to figure out what data is actually used and what is redundant.

• Semantic Acceleration: The Triple Store ingests system logs, database catalog data, and historical queries, linking them together. By running a graph traversal algorithm, ArcXA instantly spots "dead ends" (data that is never queried or moved). It identifies exactly what can be left behind, drastically shrinking the data footprint and cutting ETL compute costs.

Pillar 2: Data Selectors

• The Problem: Selecting the right data subset for migration or testing usually requires writing massive, complex SQL queries with dozens of joins.

• Semantic Acceleration: In a graph, relationships are "first-class citizens." Finding related data doesn't require complex SQL joins; it requires simple graph traversal. If you want to select a specific customer segment, the Triple Store instantly traverses the links from Customer -> Orders -> Payments -> General Ledger across the Oracle schema, pulling the exact slice of data instantly.

Pillar 3: Eval Set Generation

• Problem: Creating a representative testing/evaluation set requires understanding the semantic context of data so you don't break referential integrity.

• Semantic Acceleration: The Triple Store retains the structural and contextual meaning of the data. When generating an eval set, it ensures that if a "Subject" is selected, all its mandatory "Predicates" and "Objects" come with it. It uses semantic reasoning to generate synthetic or masked test data that behaves exactly like production data, keeping SAP and Db2 targets happy.

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3. End-to-End Sequential Flow (The Automation Loop

)

In a sequential flow from [Discovery ---> Transformation ---> Continuous Governance] a Triple Store changes the flow from a static checklist into a continuous feedback loop.

• Discovery: Instead of just scanning schemas, the Triple Store builds the initial graph, discovering hidden relationships and dependencies that human architects miss.

• Transformation & Migration: Because the graph knows what the data means (not just what it's named), it automates the "Replaces" callouts by neutralizing the need for legacy middleware or manual mapping spreadsheets.

• Continuous Governance: This is where Triple Stores shine. When the migration is done, the graph doesn't disappear. It stays active. If a rogue schema change occurs in the target Db2 or SAP instances, the semantic engine detects that a "triple" has broken or deviated from the governance policy, raising an immediate alert.

In short: The Triple Store replaces manual, hardcoded code analysis with graph analytics and semantic reasoning. It allows ArcXA to understand the data context, allowing you to click any node in your diagrams and instantly drill deeper into its upstream origins and downstream impacts.

 

4. Three connected diagrams:

ArcXA intelligence layer in the middle, and the target outputs. Each tells a distinct part of the story.

Diagram 1: The migration pipeline — Oracle as source, SAP/IBM as targets, with ArcXA sitting in the middle as the intelligence layer. 

Diagram 2: ArcXA's three core capabilities — how schema discovery, data selectors, and eval sets each work inside the migration, and what they replace. 

Diagram 3: The compound output — what ArcXA produces end-to-end, from Oracle scan through to continuous post-migration governance. Three diagrams covering the full picture :

__________________________________________________________________________________

• Diagram 1 — the pipeline view: Oracle in, ArcXA in the middle, SAP and IBM Db2 as the two targets

• Diagram 2 — the three capability pillars side by side: ETL cost reduction, data selectors, and eval set generation with their sub-functions

• Diagram 3 — the end-to-end sequential flow from discovery through to continuous governance, with "replaces" callouts on the left (what ArcXA displaces) and "output" callouts on the right (what it produces)I'll build this as three connected diagrams — the overall flow, the ArcXA intelligence layer in the middle, and the target outputs. Each tells a distinct part of the story

ETL mapping work in ArcXA?

• Diagram 4 — ArcXA Key Insights, Xplainable Assist (XA)  — "lineage-aware" actually means that ArcXA doesn't just look at a field in isolation and guess what it maps to.

• ArcXA traces how that field has been used — which queries touched it, which views joined on it, which stored procedures transformed it — and uses that usage history to propose the transformation rule. So ACCT_BAL NUMBER(15,2) in Oracle doesn't get a generic type-cast suggestion; it gets the specific rule that matches how the business has been consuming that field for years.