Meet TypeDB (and TypeQL)

TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language.

A higher level of expressivity

TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.

TypeDB enables:

• Building rich knowledge models by defining type hierarchies, hyper-entities and hyper-relations.
• Intuitively defining logical rules that produce implicit inferred knowledge based on expressive complex patterns.
• Performing built-in distributed analytics (Pregel and MapReduce) on large datasets.
• Using a high-level, easy to use and declarative query language to describe complex constructs within the data model.

Visit TypeDB.com to learn more.

Entity-Relationship Model

TypeDB allows you to model your domain using the well-known Entity-Relationship model. It is composed of entity types, relation types, and attribute types, with the introduction of role types. TypeDB allows you to leverage the full expressivity of the ER model, and describe your schema through first normal form.

Type Hierarchies

TypeDB allows you to easily model type inheritance into your domain model. Following logical and object-oriented principle, TypeDB allows data types to inherit the behaviours and properties of their supertypes. Complex data structures become reusable, and data interpretation becomes richer through polymorphism.

N-ary Relations

In the real world, relations aren't just binary connections between two things. In rich systems, we often need to capture three or more things related with each other at once. Representing them as separate binary relationships would lose information. TypeDB can naturally represent arbitrary number of things as one relation.

Nested Relations

Relations are concepts we use to describe the association between two or more things. Sometimes, those things can be relations themselves. TypeDB can represent these structures naturally, as it enables relations to be nested in another relation, allowing you to express the model of your system in the most natural form.

A higher degree of safety

Types provide a way to describe the logical structures of your data, allowing TypeDB to validate that your code inserts and queries data correctly. Query validation goes beyond static type checking, and includes logical validations of meaningless queries. With strict type-checking errors, you have a dataset that you can trust.

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 richer validation of inserted entities and relations by evaluating the polymorphic types of the things involved.

Logical Query Validation

Read queries executed on TypeDB go through a type resolution process. This process not only optimises the query's execution, but also acts as a static type checker to reject meaningless and unsatisfiable queries, as they are likely a user error.

Evolved with logical inference

TypeDB encodes your data for logical interpretation by a reasoning engine. It enables type-inference and rule-inference that creates logical abstractions of data. This allows the discovery of facts and patterns that would otherwise be too hard to find; and complex queries become much simpler.

Rules

TypeDB allows you to define rules in your schema. This extends the expressivity of your model as it enables the system to derive new conclusions when a certain logical form in your dataset is satisfied. Like functions in programming, rules can chain onto one another, creating abstractions of behaviour at the data level.

Inference

TypeDB's inference facility translates one query into all of its possible interpretations. This happens through two mechanisms: type-based and rule-based inference. Not only does this derive new conclusions and uncovers relationships that would otherwise be hidden, but it also enables the abstraction of complex patterns into simple queries.

ACID Transactions

TypeDB provides ACID guarantees, up to Snapshot Isolation, through of schema validation and consistent transactions. With lightweight optimistic transactions, TypeDB allows a high number of concurrent read and write transactions. With atomic all-or-nothing commits, transactional semantics become easy to reason over.

Visit TypeQL docs to learn more.

• Life sciences: TypeDB makes working with biological data much easier and accelerates the knowledge discovery process (for examples, read more and see Github).
• Financial Services: TypeDB allows the integration of hugely complex financial networks of data and in a simple and intuitive way.
• Security & defence: TypeDB allows security professionals to leverage complex sources of data to make decisions in defence of national security (for examples, read more and see Github).
• Robotics: TypeDB enables the creation of robotics and autonomous vehicles by enabling them to make the right behavioural decisions to achieve real-time tasks.

AGPL and Commercial.

The commercial license is priced based on cluster resources of a hosted TypeDB instance on Google Cloud Platform and Amazon Web Services. Visit TypeDB Cluster or contact our enterprise team to learn more.