DBMS > Grakn

Grakn System Properties

Please select another system to compare it with Grakn.

Our visitors often compare Grakn with Neo4j, GraphDB and Dgraph.

Editorial information provided by DB-Engines

Name

Description

Grakn is a distributed, hyper-relational database for managing complex data that serves as a knowledge base for cognitive/AI systems.

Primary database model

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.76
Rank	#193	Overall
	#17	Graph DBMS
	#97	Relational DBMS

Website

grakn.ai

Technical documentation

dev.grakn.ai/docs

Developer

Grakn Labs

Initial release

2016

Current release

2.0, April 2021

License

Commercial or Open Source

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

console (shell)
gRPC protocol
Workbase (visualisation software)

Supported programming languages

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

Grakn is the knowledge graph to organise complex networks of data and making it queryable, by performing knowledge engineering.

Grakn 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 GRAKN.AI to learn more.

Competitive advantages

Expressive and flexible data model: The meta-schema of Grakn allows for modelling the real world, that is modelling a dataset the exact same way as it is perceived in reality.
Logical integrity: The expressivity of the data definition language in Grakn enables the integrity and consistency of the data beyond what is offered by any other database.
Machine reasoning: Rules in Grakn and type hierarchies defined within the schema set the basis for reasoning over explicitly stored data to discover deeply hidden insights.
Optimised query execution: Graql reduces the time and complexity of writing highly expressive queries while Grakn optimises the query traversal.
Analytics out of the box: The underlying model of Grakn allows for applying distributed graph analytics on the entire dataset as well as its subgraphs.

Visit Grakn and Graql to learn more.

Typical application scenarios

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

Licensing and pricing models

AGPL and Commercial.

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

News

Today’s Biomedical Research Requires New Technologies
12 March 2021

A Clinical Decision Support System Built With a Knowledge Graph
16 February 2021

You’re Invited to Grakn Orbit 2021
12 February 2021

How to Succeed with Your First Grakn Project
12 February 2021

Grakn 2.0 Alpha: best practices of Distributed Systems and Computer Science
13 January 2021

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Conferences and events

more DBMS events

Grakn Orbit 2021
Online Event, 21-22 April 2021

Recent citations in the news

Bayer, Capgemini, IBM and Flipkart Lead Roster of Speakers and Panelists at Grakn Orbit 2021
31 March 2021, WFMZ Allentown

Get Started With GRAKN.AI
10 March 2017, DZone News

GRAKN.AI: How Haikal Pribadi went from being a refugee to building a database for AI systems
26 October 2017, YourStory.com

What Is an Ontology?
15 March 2017, DZone News

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

provided by Google News

Share this page