Oracle's master data capabilities are split across Fusion Cloud: Customer Data Management inside CX, Product Hub inside SCM, and Enterprise Data Management Cloud for hierarchies and dimensions across applications.
Every Oracle cell carries its source number; the sources are listed at the foot of the page.
| Question | Oracle | Lima master data |
|---|---|---|
| Where the master data lives | Customer and product data live inside the Fusion pod (CX and SCM); Enterprise Data Management keeps nodes and hierarchy sets per application and copies them to each subscriber through exports and subscriptions [1][2][3]. | Golden records are governed views over the sources, read in place through the federated engine, and materialised only where latency needs it, in your lake, under the same keys. The transactions sit in the same bed, so a merged customer and its orders change together. |
| Reaching SAP, Oracle and the lakes | Native for Fusion transactions; other systems connect through REST, import management and the EDM subscriptions; the E-Business Suite keeps Premier Support through at least 2037, so there is no forced move [4][5]. | SAP S/4HANA and ECC through released read interfaces and change capture; Oracle Fusion through REST and BI Cloud Connector extracts, E-Business Suite through JDBC and open interfaces; Snowflake, Databricks and Fabric read in place; Salesforce, ServiceNow and Workday through their APIs. Write-back through BAPIs, IDocs, REST and web services, acknowledged and logged. |
| Golden record: matching and survivorship | CDM: real-time duplicate identification through Enterprise Data Quality, resolution by linking or merging, survivorship through 'Set Master Record' and 'Set Attribute Value' rules in Groovy or Business Rules, agreement rules that block invalid merges [1]. | Strong keys first (VAT ID, DUNS, GTIN, manufacturer part number), then standardised attribute and address matching, with a language model for the hard pairs; two thresholds per rule (review, merge); survivorship per field by source rank, recency, verification and steward override; unmerge restores the sources; every value keeps its source, rule and time. |
| Hierarchies and reference data | EDM: viewpoints, node types, alternate hierarchies (four patterns), constraints at request and commit time with severities, 'compare and rationalize', request history and node history; a limit of four unique-property constraints per application [2][3]. | Levels and several hierarchies per entity, kept as versions with validity dates and validated against the facts they aggregate; reference data and crosswalks kept as small domains with the same history, rules and security. |
| Rules, security and audit | Fusion role, privilege and data-security policies; CDM profile history with changed and rejected attributes and survivorship results; EDM change audit and request subscriptions [1][2]. | Column, row and business rules in one language, evaluated on save and on demand, including rules over aggregates and across tables; twelve security layers for read, write and delete; an append-only audit trail with point-in-time reads and logged reads of sensitive columns. |
| APIs and data services | REST resources per object, including a findDuplicates action for accounts and contacts; the SOAP real-time data-quality service is deprecated; EDM REST and flat-file interfaces [6][3]. | REST, SOAP, SQL (JDBC and ODBC), events and an agent endpoint over one policy engine; the golden-record lookup answers with the record, the cross-reference and live related facts; page sizes and rate limits published per endpoint. |
| Analytics: pivots, measures, transactions | Oracle EPM Planning owns pivots, grid spread and time spreading (proportional, even, fill, 4-4-5); those features sit outside the master-data products [7]. | Pivots on any hierarchy level with time on the columns and measures in the cells; calculated measures; data entry with disaggregation by weights, equal shares or a time profile; drill-down from a cell to the transactions and to the source row; charts beside grids; natural-language and SQL querying. |
| Pricing unit and trial | Metrics: CDM 'Hosted Named User', Product Hub and EDM 'Hosted 1,000 Records'; prices unpublished; no trial on the EDM page; '78% of EDM customers surveyed improved their productivity' [8][3]. | Platform capacity tiers (32C to 128C); domains, records, attributes and users included; the price is written before the work starts; a guided first domain on your data in one day; the showcase estate for demonstrations; a self-service sandbox tier is a decision pending (see the review notes). |
| Analyst placements 2025–26 | Oracle appears in the ISG Buyers Guide MDM 2025 as an Overall Leader; the 2026 Gartner MQ for MDM Solutions lists no Oracle entry [9][10]. | Analyst evaluation is the purpose of this page set; placements to date: none. The platform pages are organised on Gartner's eight mandatory features and four implementation styles so a briefing lands in the right market. |
Choose Oracle when the enterprise runs Fusion Cloud end to end and wants master data governed inside those applications, and when Enterprise Data Management's request-based hierarchy changes fit the finance organisation. Its native integrity with Fusion transactions and the EDM viewpoint model are real advantages for an Oracle-standardised organisation [2].
Lima suits the enterprise whose master data should be governed on the rows in place across SAP, Oracle, the CRM and the lakes, with the transactions in the same bed: the golden record and its orders in one query, rules over totals, pivots on golden dimensions with data entry and disaggregation, drill-downs to the source row, and a headless lookup that answers with live related facts. Twelve security layers and an append-only audit trail apply to every door, and the price is written before the work starts.
The domain catalogue shows thirty domains with, for each, the objects read in place in SAP S/4HANA, Oracle Fusion, Salesforce, Workday, ServiceNow, Snowflake and Databricks and the interface used for the write-back.
Facts change; re-check the sources at each review and re-date the page.
Bring two systems that hold the same customers, suppliers or materials. In one working day we connect them, run the match on live rows, review the queue with your steward and publish the first golden view with its API.
