Expressivity

Entity-Relationship Model

TypeDB allows users to model their domains using the entity-relationship (ER) model. It is composed of entity types, relation types, and attribute types, with the introduction of role types. TypeDB empowers users to harness the complete expressiveness of the Entity-Relationship (ER) model, enabling them to describe schemas with precision through first normal form.^[4]

Type Hierarchies

TypeDB allows users to model type inheritance into their domain model. Following logical and object-oriented principles, TypeDB allows data types to inherit the behaviors and properties of their super types. Complex data structures become reusable, and data interpretation becomes richer through polymorphism.

N-ary Relations

Relations often aren't just binary connections between two things. In complicated systems, three or more things can be related with each other at once. Representing them as separate binary relationships would cause a user to lose information. TypeDB can represent an arbitrary number of things as one relation.

Nested Relations

Relations are concepts used to describe the association between two or more things. Sometimes, things can be relations themselves. TypeDB can represent such a structure, as it enables relations to be nested in another relation, allowing a user to express their system's model in a natural form.

Safety

Logical Data Validation

Inserted data gets validated beyond static type-checking of attribute value types. Entities are validated to only have the correct attributes, and relations are validated to only relate things that are logically allowed. TypeDB performs validation of inserted entities and relations by evaluating the polymorphic types of the things involved.

Logical Query Validation

Queries executed on TypeDB undergo a type resolution process. This process not only optimizes query execution but also serves as a static type checker. Its role is to identify and reject queries that are meaningless or unsatisfiable, often indicating user errors.

Logical inference

Rules^[5]

TypeDB allows users to define rules within their schemas. This feature enhances the expressiveness of the model by enabling the system to derive new conclusions when specific logical conditions within a dataset are satisfied. Similar to functions in programming, rules can be chained together, allowing the creation of abstractions related to data-level behaviors.

Inference

TypeDB's inference capabilities encompass the translation of a single query into all its potential interpretations. This occurs through two key mechanisms: type-based inference and rule-based inference. These processes yield fresh insights, reveal concealed relationships, and facilitate the simplification of intricate patterns into straightforward queries.

TypeDB

TypeDB is a database with a rich and logical type system. Under the hood, TypeDB has built an expressive type system with a transactional query interface. TypeDB’s type system is based on hypergraph theory, a subfield in mathematics that generalizes an edge to be a set of vertices.^[6] The hypergraph data structure itself is represented in the form of key-value pairs and persisted on a distributed NoSQL database, RocksDB. Using the Raft algorithm, TypeDB provides a distributed system designed to be shared and replicated over a network of computers.

TypeQL

TypeQL is TypeDB’s declarative reasoning (through OLTP) query language that creates a higher level abstraction over complex relationships. TypeQL allows users to derive implicit information that is hidden in a dataset, as well as reduce the complexity of that information.