Typedb

TypeDB is a strongly-typed graph database and knowledge graph management system. It serves as a multi-model data store that unifies relational, document, and graph structures into a single environment, functioning as both an ACID compliant database and a declarative query engine.

The system distinguishes itself through the use of n-ary hypergraph modeling and polymorphic type hierarchies. It employs a strongly-typed schema to enforce structural rules and validate data integrity, allowing for type-based polymorphic inference and role-based interface polymorphism to resolve complex relationships automatically during query execution.

The platform covers a broad range of capabilities including the computation of recursive relationships via tabling, snapshot-isolation transactions, and declarative data retrieval. It also supports high availability through consensus-based cluster replication, role-based access control, and integration with AI agents for structured data retrieval.

Management is supported via a command-line interface, and the system provides tools for visualizing graph schemas and auditing administrative activity.

Features

Knowledge Graphs - Implements a strongly-typed system for building knowledge graphs that map complex semantic relationships between entities.
Hypergraph Modeling - Employs n-ary hypergraph modeling to represent complex relationships connecting multiple entities and attributes.
Knowledge Graph Management - Functions as a comprehensive system for managing interconnected data as nodes and edges to model complex information domains.
ACID Transactional Cores - Ensures database consistency and integrity through a core engine that provides ACID-compliant transaction processing.
Snapshot Isolation Techniques - Ensures database consistency and isolation through snapshot-isolation ACID transactions.
Atomic Transaction Execution - Processes reads, writes, and schema changes as isolated atomic units to guarantee database safety.
Database Schema Constraints - Implements strict database-level schema constraints to ensure logical consistency and structural integrity.
Database Transaction Management - Provides programmatic control over the lifecycle of data operations to ensure consistency and stability.
Declarative Query Engines - Features a declarative query engine that uses high-level patterns and polymorphic inference to find data without specified paths.
Declarative Query Languages - Provides a declarative query language to retrieve information using polymorphic patterns without specifying exact paths.
Declarative Query Pipelines - Provides a declarative query pipeline using polymorphic clauses to navigate complex relationships without specifying exact paths.
Declarative Schemas - Provides a declarative language to create structural blueprints that validate all subsequent data reads and writes.
Type Hierarchies - Supports the definition of polymorphic type hierarchies where specialized types inherit properties from supertypes.
Entity Relationships - Manages intricate data dependencies and polymorphic hierarchies where entities share common roles.
Graph-Relational Models - Unifies relational, document, and graph structures into a single, strongly-typed multi-model environment.
Strongly-Typed Graph Databases - Functions as a strongly-typed graph database that validates all data and queries against a strictly enforced schema.
Hypergraph Modeling - Implements a hypergraph structure where relations connect any number of objects and possess their own attributes.
Multi-Model Databases - Unifies relational, document, and graph data models into a single, strongly-typed storage environment.
Complex Data Modeling - Organizes intricate information using a combination of relational, document, and graph structures.
Polymorphic Relations - Implements polymorphic relations where multiple distinct types can be mapped to a single role within a relation.
Semantic Query Validation - Enforces strict structural rules to identify and prevent logically impossible queries before they are executed.
Interconnected Data Retrieval - Enables retrieval of interconnected information by navigating complex relationship paths across diverse data models.
ACID-Compliant - Provides a storage engine that ensures atomic, consistent, isolated, and durable operations.
Structured Data Schemas - Provides tools for defining complex, strongly-typed data structures using entities and role-based relations.
Structured Data Modeling - Enables the construction of strongly-typed data models using entities and relations to enforce structural integrity.
Type-Based Polymorphic Inference - Automatically resolves subtypes and inherited properties during query execution to retrieve data across hierarchical structures.
Subtype Inheritance - Establishes subtyping hierarchies where specialized types inherit all interfaces and implementations from a supertype.
Data Schema Validation - Enforces type safety and data consistency by validating inserted data against the defined schema.
Strongly-Typed Schema Validation - Enforces a strongly-typed schema to validate all read and write operations against a structural blueprint.
Role-Based Interface Polymorphism - Implements role-based interface polymorphism to allow different entity types to be used interchangeably within a single relation role.
Subtype Hierarchies - Supports subtype hierarchies that allow queries to automatically handle inherited data types via polymorphism.
Schema-Driven Relationship Inference - Automatically resolves types and subtypes using a typed schema to remove the need for manual query updates.
Agentic Data Integrations - Provides structured data retrieval and machine-readable schemas for integration with AI agents and automation frameworks.
Attribute Constraints - Enforces data integrity using keys, uniqueness constraints, cardinality limits, and range restrictions on attributes.
Data Value Restrictions - Enforces cardinality and value restrictions on attributes to ensure data correctness during insertion.
Horizontal Scaling - Distributes data across server clusters to provide horizontal scalability and increased read capacity.
Polymorphic Data Operations - Supports inserting, updating, and deleting data across multiple types and hierarchies using unified operations.
Query Abstraction Layers - Defines functions that encapsulate complex data lookups as a higher level of abstraction.
Query Execution Pipelines - Utilizes a declarative query pipeline to chain clauses for retrieving data across diverse data models.
Recursive Relationship Querying - Computes transitive closures and recursive relationships using tabling to prevent infinite loops during retrieval.
Tabling-Based Recursive Computation - Computes recursive relationships and transitive closures using tabling to cache intermediate results and prevent cycles.
Semantic Query Validation - Analyzes read and write operations against the schema to identify logically unsatisfiable queries before execution.
Schema-Integrated Logic Abstractions - Captures complex logic within the schema to simplify queries and automate the inference of data.
Consensus-Based Replication - Implements distributed consensus algorithms to ensure high availability and data synchronization across cluster nodes.
Database High Availability - Ensures continuous service availability across nodes using a replication system based on consensus algorithms.
Database Access Controls - Implements role-based access control to restrict database access to authorized principals.
Query Logic Encapsulation - Allows wrapping recurring data request patterns into reusable functions to simplify complex operations.
Transactional Migration Managers - Executes schema migrations within atomic transactions to maintain data integrity during model updates.

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Features