Noreja vs. mpmX Comparison
mpmX from German vendor MEHRWERK is tightly interwoven with Qlik technology, reliably resolves complex n:m relationships, and works in-memory for highly interactive analysis. This comparison shows the technological distinction: mpmX builds on an associative BI engine and remains frequency-based in its process analysis. Noreja, by contrast, relies on a dedicated, graph-based causal and temporal model, thereby separating genuine causes from statistical coincidence.
Comparison at a Glance
| Criterion | Noreja | mpmX |
|---|---|---|
| Analysis paradigm | Causal + Temporal | Frequency-based |
| Data model | Event Knowledge Graph | Data-platform-native model (Qlik/Snowflake/Databricks), OCPM |
| Ecosystem lock-in | Low | High |
| Causal analysis | Native | No |
| Enterprise AI capability | High | MediumWith object-centric process mining in its standard scope, mpmX captures multiple object types and thus provides usable context; however, the model lives on the respective data platform and is not maintained as a dedicated knowledge graph extensible with documents and enterprise knowledge. |
| Pricing transparency | Transparent, public | On request |
About mpmX
mpmX from German vendor MEHRWERK brings process mining directly onto existing data platforms: data preparation, storage, and mining run natively on Qlik, Snowflake, or Databricks. Object-centric process mining (OCPM) is part of the standard scope, and the self-service approach enables data-savvy teams to start quickly.
Strengths
- Reliably resolves complex n:m relationships between process objects
- Data-platform-native: preparation and mining directly on Qlik, Snowflake, or Databricks
- Object-centric process mining (OCPM) as part of the standard scope
- Fast onboarding and self-service for data-savvy departments
Methodical context
- Analytical strength is tied to the foundation of the respective data platform
- Despite OCPM, process analysis remains frequency-based without causal modeling
- No graph-based, semantic causal model at its core
Why Noreja instead of mpmX?
Noreja relies on a dedicated, graph-based causal and temporal model instead of a frequency analysis built on top of BI and data platforms – thereby separating genuine causes from statistical coincidence.
Additional Noreja advantages
- Explicit semantics of business relationship types: the Event Knowledge Graph distinguishes temporal, causal, and contextual paths and links rules, SOPs, and documents with the process data – beyond resolving object relationships.
- A knowledge base independent of the data platform: analysis and context model live in a dedicated graph rather than in apps of a BI or data-platform engine – so the usage layer is not tied to Qlik, Snowflake, or Databricks.
Frequently Asked Questions
Is Noreja an alternative to mpmX (MEHRWERK)?
Yes. Both address process mining, but Noreja relies on a graph-based causal model instead of a frequency-based analysis built on Qlik.
Do I need Qlik to use Noreja?
No. Noreja brings its own graph and analysis infrastructure. mpmX, on the other hand, is tied to the Qlik technology foundation.
How does Noreja handle n:m relationships?
Noreja represents n:m relationships natively in the Event Knowledge Graph and augments them with causal and temporal links – beyond relational resolution alone.
More comparisons
Experience Causal Process Analysis Yourself
See how Noreja analyzes processes causally on an Event Knowledge Graph – beyond frequency-based Directly-Follows models.