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Not covered by Lakebridge, Cortex conversion, or BigQuery Migration Service. Targets delivered: Databricks, Snowflake, BigQuery.

Convert Oracle Data Integrator mappings to modern pipelines

Parser-driven modernization of ODI repository XML and Smart Export bundles — mappings, packages, load plans, and knowledge modules. Full lineage, automated conversion, validated parity.

MigryX analyzer showing a parsed Oracle ODI mapping as an interactive lineage graph ODI mapping parsed into interactive lineage graph
Architecture

Oracle ODI in. Native platform out.

One source, every target. Deterministic parsers read the estate and emit native code for the platform you pick — not ODI mappings lifted into a hosted ODI.

Oracle ODI estate → MigryX parser → native platforms

Oracle ODI
MappingsInterfaces
PackagesSerial + loops
Load plansParallel steps
Knowledge modsLKM / IKM / CKM
MigryX Parser
Deterministic parseAI where it helps
Lineage / STTMBefore cutover
KM rewriteNative SQL/Spark
Interface graphSource-to-target

The parser is deterministic: the same input produces the same output on every run. Every output is validated against the original, row by row, before go-live.

Why now

The logic isn't in the mappings

Knowledge Modules hold the behaviour

A mapping shows intent, but the SQL that runs is generated by its IKM, LKM and CKM at execution time. Reading the mappings alone tells you what was meant, not what happened, which is why ODI estates are hard to inventory honestly.

The topology is a second system to migrate

Contexts, data servers, physical and logical schemas, and agents form an environment layer that lives outside the mappings. It has to be reproduced or replaced before a single converted job can run.

Studio and repository skills are scarce

ODI development requires the Studio client and a master/work repository pair. Teams that inherited an ODI estate often have nobody who can safely change a KM, so the estate freezes and workarounds accumulate around it.

See it in action

IKM Incremental Update — where the generated SQL lives

An incremental-update integration knowledge module with flow control. The mapping never states the staging table, the update key comparison, or the reject handling — the KM generates all of it. MigryX resolves the KM to the SQL it would have produced.

Oracle ODI (repository export)
-- Mapping: LOAD_CUSTOMER_DIM
-- IKM: Oracle Incremental Update
-- LKM: SQL to Oracle
-- CKM: Oracle (flow control enabled)

Source datastores : CRM_CUSTOMER, CRM_ADDRESS
Join              : CUSTOMER.ADDR_ID = ADDRESS.ADDR_ID
Filter            : CUSTOMER.STATUS <> 'PURGED'
Target datastore  : CUSTOMER_DIM
Update Key        : CUST_NK
Mappings          : FULL_NAME = FIRST_NM || ' ' || LAST_NM
                    CITY      = ADDRESS.CITY

-- KM behaviour, not visible in the mapping:
--   1. load into I$_CUSTOMER_DIM staging
--   2. flow control writes violations to E$_CUSTOMER_DIM
--   3. update matched rows, insert unmatched by CUST_NK
MigryX
converts
Snowflake SQL
-- IKM Incremental Update → MERGE
CREATE OR REPLACE TEMPORARY TABLE i_customer_dim AS
SELECT  c.cust_nk,
        c.first_nm || ' ' || c.last_nm  AS full_name,
        a.city                          AS city
FROM    crm_customer c
JOIN    crm_address  a ON c.addr_id = a.addr_id
WHERE   c.status <> 'PURGED';

-- CKM flow control → explicit reject capture
INSERT INTO e_customer_dim
SELECT * FROM i_customer_dim WHERE cust_nk IS NULL;

MERGE INTO customer_dim t
USING (SELECT * FROM i_customer_dim
       WHERE cust_nk IS NOT NULL) s
   ON t.cust_nk = s.cust_nk
WHEN MATCHED THEN UPDATE
   SET t.full_name = s.full_name, t.city = s.city
WHEN NOT MATCHED THEN INSERT
   (cust_nk, full_name, city)
   VALUES (s.cust_nk, s.full_name, s.city);

The I$ staging step, the E$ reject table from flow control, and the update-key comparison all become explicit SQL. What the KM used to generate at runtime is now readable code you can review and version.

Coverage

What gets converted

Every ODI artifact in the export maps to a defined target equivalent, recorded in the lineage report.

ODI Component Target Equivalent Notes
Mapping / reusable mappingTransformation pipelineDatasets, joins, filters and expressions
IKM (integration)MERGE or insert/appendIncremental update resolved to an update key
LKM (load)Staged extract and loadLoading strategy mapped to target staging
CKM (check)Constraint checks and reject tableE$ error flow becomes explicit capture
PackageOrdered driver with step logicStep sequence, ok/ko branches preserved
Load planOrchestrated DAGSerial and parallel steps, restart points
ScenarioVersioned executable jobGenerated scenario resolved to its source
Variable / sequenceParameters and generated keysRefresh queries and scope preserved
Procedure / SQL overrideParameterized SQL stepMulti-technology commands separated
Model and datastoreTarget schema definitionDatatypes and constraints carried over
Topology / contextEnvironment config and secretsLogical to physical resolution per context
Agent invocationScheduler entryStartScen calls mapped to the orchestrator
Validation

Every conversion is validated to row-level parity

MigryX Data Matching compares ODI mapping output against the new pipeline output, row by row and column by column, with configurable tolerance rules and mismatch drill-down.

See how Data Matching works →
FAQ

Oracle ODI modernization questions

What do you need from the ODI repository?

A Smart Export from ODI Studio, or an XML export of the projects and models in scope. Smart Export is preferred because it follows dependencies and brings the related models, KMs and topology references with the mappings.

How do you handle custom or modified Knowledge Modules?

Custom KMs are parsed as first-class inputs rather than assumed to match the shipped versions. Because the KM determines the SQL that actually ran, a modified KM changes the generated output, and it is reported with the mappings that use it so the difference is visible before conversion.

Do load plans and packages keep their restart behaviour?

Step order, ok/ko branching and restart points are carried into the target orchestrator. Where ODI relied on agent-level behaviour that has no direct equivalent, that step is flagged for review rather than silently approximated.

Can we migrate project by project?

Yes. Export and convert one project or a set of mappings, validate to parity, and repeat. This matters in ODI estates because the topology layer can be reproduced once and reused across subsequent waves.

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