FactEngine leverages the knowledge that all databases are multi-model bar for thinking differently about what a database is. FactEngine strips back the marketing material of various database types and exposes to you that your data warehouse is already multi-model and accessible to graph analytics.
Knowledge engineering in FactEngine is written in FactEngine Knowledge Language (FEKL) and Object-Role Modeling, types of fact-based modelling. FactEngine Knowledge Language leverages over 30 years research and development into the application of fact-based modelling to enterprise/conceptual modelling and logic.
Knowledge graphs captured in fact-based modelling are database type agnostic. This means that when you capture your business domain model in FEKL and Object-Role Modeling you automatically have a graph and relational model to work over, and have captured your business rules in business language. FactEngine exploits this capability by delivering graph queries over your data warehouse/database in business language and automatically as graph queries.
The cost saving of FactEngine are achieved by dispensing with the notion that you may need to purchase license agreements for dedicated graph databases when you can achieve the same aim on your existing relational or document database. The added benefit of FactEngine is that if you do have a graph database, then you can query that database in business language as well.
Here is an example of traversing a knowledge graph and viewing the same underlying model as a property graph schema, a relational model or an object-role model:
Here is a video of querying a relational database with a graph query in business language: