Stibo Systems' STEP is a multidomain platform with its roots in product information management, delivered as multi-tenant SaaS on Azure, with ProductGen AI, machine-learning match recommendations and an MCP server launched on June 29, 2026.
Every Stibo Systems cell carries its source number; the sources are listed at the foot of the page.
| Question | Stibo Systems | Lima master data |
|---|---|---|
| Where the master data lives | Master data lives in the STEP repository (products, entities, classifications, assets, publications); inbound integration endpoints load it and outbound endpoints publish it to channels, Kafka, files and REST receivers [1][2]. | 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 | '100+ prebuilt connectors' on the platform page; reviewers describe downstream integrations that 'function as projects' and heavy modelling effort [3][4]. | 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 | Two match actions: Match and Link (golden records aggregated from source records and left unedited) and Match and Merge; golden-record survivorship rules; Machine Learning Match Recommendations trained on clerical-review decisions [5][6][7]. | 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 | A semantic data graph with typed relationships and configurable hierarchies; products appear in several classification hierarchies through references; attribute inheritance [8][1]. | 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 | JavaScript business rules and attribute validations; privilege rules per group by action, object type, node, attribute group and workflow state; revisions kept with timestamp and user, with historic reporting run as a background function [9][10][11]. | 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 API V2 and inbound/outbound integration endpoints (REST, Kafka, SQS); the MCP Server gives agents read access to 'semantic relationships, hierarchies, and data governance rules' [2][12]. | 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 | Homepage widgets and profiling; analytics described by a reviewer as 'too shallow'; pivots and measures are absent [13][4]. | 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 | Pricing, trial and demo forms are absent from the platform page; reviewers describe per-user licence fees with paid customisations; a Microsoft Marketplace SaaS listing exists [3][14]. | 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 | Gartner Magic Quadrant for MDM Solutions, April 6, 2026: Leader ('the largest independent provider'); Forrester Wave MDM Q2 2025: Leader; G2 High Performer Fall 2026 [15][16]. | 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 Stibo Systems when product experience data (syndication, digital shelf, assets) is the centre of the programme, when a large retail or manufacturing catalogue needs deep classification and channel publishing, and when an independent vendor on Azure is preferred. Its retail references and 50-year record are real advantages for a product-first buyer [15].
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.
