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What is Grakn?

The cornerstone of developing intelligent systems is the database, with Grakn exemplifying a highly advanced knowledge graph database. It boasts a remarkably intuitive and expressive data schema, enabling the creation of hierarchies, hyper-entities, hyper-relations, and rules for constructing comprehensive knowledge models. Grakn employs an intelligent language that performs logical inferences on various data types, relationships, attributes, and complex patterns in real-time across both distributed and stored data. Additionally, it includes integrated distributed analytics algorithms, such as Pregel and MapReduce, which users can easily access through simple queries within the language. The system abstracts low-level patterns effectively, making it easier to articulate intricate constructs while ensuring that query execution is optimized automatically. By utilizing Grakn KGMS and Workbase, businesses can efficiently expand their knowledge graphs. Moreover, this distributed database is designed to operate optimally across a network of computers by employing strategies like partitioning and replication, which guarantees consistent scalability and performance. Ultimately, Grakn not only streamlines the management of complex data but also enhances the overall capability of intelligent systems.

What is Cayley?

Cayley is an open-source database specifically designed for Linked Data, inspired by the graph database that underpins Google's Knowledge Graph, which was formerly known as Freebase. This database prioritizes user-friendly design while effectively managing complex data structures; it includes a built-in query editor, visualizer, and Read-Eval-Print Loop (REPL) functionality. It supports a variety of query languages, such as Gizmo, which is modeled after Gremlin, a query language similar to GraphQL, along with MQL, a simplified version aimed at Freebase users. With its modular architecture, Cayley seamlessly integrates with preferred programming languages and backend storage solutions, making it production-ready and well-tested, with numerous companies relying on it for their operational needs. Furthermore, its optimization for application use showcases remarkable performance; for example, it has been demonstrated to handle 134 million quads in LevelDB on standard 2014 hardware, with multi-hop intersection queries—like identifying films featuring both X and Y—executing in around 150 milliseconds. By default, Cayley operates in-memory, reflecting the capabilities of its backend memstore, which significantly boosts its speed and efficiency during data retrieval and manipulation. Overall, Cayley stands as a robust solution for developers aiming to harness linked data in their applications, while its continuous improvements and community support ensure it keeps pace with evolving technological demands.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform

Integrations Supported

Docker
GraphQL
KeyLines
Kubernetes
ReGraph

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Mac
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Grakn Labs

Date Founded

2016

Company Website

grakn.ai/

Company Facts

Organization Name

Cayley

Company Website

github.com/cayleygraph/cayley

Categories and Features

Distributed Databases

Not specified

Graph Databases

Not specified

Categories and Features

Graph Databases

Not specified

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