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What is RelationalAI?

RelationalAI stands at the forefront of database technology, specifically designed to optimize advanced data applications utilizing relational knowledge graphs. By emphasizing a data-centric approach to application development, it seamlessly integrates data with logic into modular structures. These advanced applications are adept at understanding and leveraging every relationship within a given model. Utilizing a knowledge graph framework, the system articulates knowledge through executable models that can be easily expanded with declarative programs, which are both accessible and user-friendly. The versatile declarative language offered by RelationalAI allows developers to significantly reduce the amount of code needed, achieving reductions between 10 to 100 times, which in turn accelerates application development and improves quality by enabling non-technical users to participate in the creation process while simultaneously automating intricate programming tasks. By harnessing a flexible graph data model, users can establish a strong data-centric infrastructure. Moreover, the integration of various models facilitates the discovery of new relationships, effectively breaking down barriers that separate different applications. This pioneering methodology not only enhances the efficiency of development but also encourages collaboration across multiple domains, ultimately creating a more interconnected ecosystem for innovation. In this way, RelationalAI is redefining the standards for how data applications are built and utilized.

What is CubicWeb?

The first and foremost step in your workflow should be to model your data, as applications might change over time, but the data itself remains a stable foundation. Once your model is effectively implemented, your CubicWeb application will be functional, enabling you to progressively add beneficial features for your users. RQL, which is derived from your application model, is a succinct language that highlights the attributes and relationships present within the data. Although it bears resemblance to SPARQL, RQL is typically regarded as more accessible for users. After a RQL query extracts a data graph, multiple views can be utilized to showcase the information in the most relevant manner. This design philosophy is crucial to the overall architecture of CubicWeb. Permissions are meticulously specified within the data model, ensuring a high level of accuracy. Additionally, every RQL query submitted to the engine is subjected to security checks to guarantee safe data handling practices. CubicWeb employs a traditional SQL database for data storage and management, with PostgreSQL being the preferred option for many users. By capitalizing on these features, CubicWeb not only improves functionality but also emphasizes the importance of security and data integrity. Ultimately, the careful integration of these aspects leads to a robust environment for application development.

Media

Media

Integrations Supported

Python

Integrations Supported

Python

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

RelationalAI

Company Location

United States

Company Website

relational.ai/

Company Facts

Organization Name

CubicWeb

Company Website

www.cubicweb.org

Categories and Features

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

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