TypeDB Fundamentals

Technical articles on the fundamentals of TypeDB and TypeQL

Engineering challenges

“Complexity will only increase in the years ahead, essentially requiring new declarative programming models focused on intent, the user, and business logic” — Amin Vahdat, Google (VP of Systems and ML)

Functional database programming

TypeDB provides users with a high-level database programming model, that infuses database engineering with powerful functional programming and pattern-matching techniques.

This series is part of our TypeDB 3.0 preview!

Modular database programming using functions

Functions provide powerful abstractions of query logic, which can be nested, recursed, or negated, and they natively embed into TypeQL's declarative patterns.

Handling data series and serialized query results with lists

Lists are a core part of the functional database programming model, and address two issues in one go: storing data series and serializing data results!

Structured values for compound attributes

TypeDB 3.0 support the use structured value types, a.k.a. structs. This drastically enhances modeling expressivity by enabling users to work with their custom compound attributes.

Constraint language for advanced data modeling

Learn about the constraint language of TypeDB's functional database programming model.

Creating complex DB workflows with pipelines

In this article we describe how, from a set of basic query operations, complex data pipelines can be crafted in TypeDB.

Flexible patterns via optionality

Learn keywords and patterns to work with optional variables in streams. Optionality significantly enhances the expressivity of patterns, adds clarity to queries, and reduces code repetition.

Understanding variables, bindings, and type-checking in TypeDB

Learn about the simple design principles underlying keywords, variables and bindings, and type-checking of TypeQL patterns.

Streamlining clauses for schema and data migration

In this article we will learn how TypeDB enables the frictionless migration of your database schema and its data through queries natively written in TypeQL.

Core features

TypeDB is based on a novel data model and querying paradigm, which sets the scene for a long list of powerful new features.

TypeDB: a New Kind of Database

Explore TypeDB's core features in detail, including validated polymorphic data models and declarative querying, and learn about their impact on database engineering.

The Conceptual Data Model of TypeDB

A conceptual data model is a starting point that must be translated into a logical model. As TypeDB uses the PERA model, the conceptual model can be directly implemented without translation.

The Type-Theoretic Language of TypeDB

TypeQL is the type-theoretic query language of TypeDB, allowing for highly expressive querying power beyond the capabilities of other modern database paradigms.

The Strong Type System of TypeDB

The backbone of TypeDB is its strong type system, which powers the resolution of declarative polymorphic queries to determine the possible return types, and the semantic validation of data.

The Symbolic Reasoning Engine of TypeDB

TypeDB's rule inference allows the database to generate new facts based on existing data and user-defined rules. This enables us to create convenient abstractions and capture complex business logic.

Data modeling

TypeDB's award-winning data model may look intricate at first, but is grounded in a few simple ingredients that apply to a large variety of data structures.

A Quick Overview of TypeDB's Data Model

Learn about the conceptual Polymorphic Entity-Relation-Attribute model that backs TypeDB and TypeQL, and how it subsumes and surpasses previous database models.

From Concepts to Types in Databases

Learn about the general conceptual principles of data organization, and how these principles are made rigorous via types, covering the key terminology used describe TypeDB's data model.

The PERA Model: an In-Depth Guide

Learn about the individual components of the Polymorphic Entity-Relation-Attribute model, and how these components can be efficiently and naturally accessed through TypeQL.

TypeDB's Data Model: a Comparison

Based on the primitives of TypeDB's polymorphic data model, we often find that migration to TypeDB from other databases becomes a simple and straightforward task.

Theoretical foundations

TypeDB and its query language, TypeQL, are firmly rooted in the study of type systems and take close inspiration from modern programming language theory.

Learn more

Interested in learning more about TypeDB and TypeQL?

Start building with TypeDB

Cloud or container, a polymorphic database with a conceptual data model, a strong subtyping system, a symbolic reasoning engine, and a type-theoretic language is minutes away.

Deploy

Learning Center