View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Knowledge Modeling Property Graph Schema Design |  Product Strategy Lean Canvas |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
Purposedifferent | Property Graph Schema Design turns business and technical requirements into a robust graph schema. It fits when query patterns, constraints, and migrations need to be thought about together. | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 4-8 h initial, dann iterativ | 45-90 min | Halber Tag pro Domain Slice | 2-4 h |
Participantsdifferent | 1-6 | 1-6 | 1-4 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Schema Diagram, Node and Relationship Catalog, Index Plan, Migration Scripts, Sample Queries | Lean Canvas, Core Assumptions, Experiment Backlog | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphModelingSemantic | StartupLeanAssumptionsBusiness model | Knowledge graphValidationSemantic | OntologyKnowledge graphScopeRequirementsSemantic |