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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The initial step in your process should always be modeling your data, as applications may come and go, but data remains constant. After successfully implementing your model, your CubicWeb application will operate, allowing you to gradually introduce valuable features for your users. RQL, which is based on your application model, is a concise language that emphasizes the attributes and connections inherent in the data. While it shares similarities with SPARQL, RQL is generally more user-friendly. Once a RQL query retrieves a data graph, various views can be applied to present the information in the most pertinent format. This design principle is fundamental to the entire CubicWeb architecture. Permissions are intricately defined within the data model, allowing for exceptional precision. Furthermore, any RQL query made to the engine automatically undergoes security checks to ensure safe handling. CubicWeb utilizes a conventional SQL database for data storage and management, with PostgreSQL being the favored choice among its users. By leveraging these capabilities, CubicWeb not only enhances functionality but also prioritizes security and data integrity.

Description

PostgresML serves as a comprehensive platform integrated within a PostgreSQL extension, allowing users to construct models that are not only simpler and faster but also more scalable directly within their database environment. Users can delve into the SDK and utilize open-source models available in our hosted database for experimentation. The platform enables a seamless automation of the entire process, from generating embeddings to indexing and querying, which facilitates the creation of efficient knowledge-based chatbots. By utilizing various natural language processing and machine learning techniques, including vector search and personalized embeddings, users can enhance their search capabilities significantly. Additionally, it empowers businesses to analyze historical data through time series forecasting, thereby unearthing vital insights. With the capability to develop both statistical and predictive models, users can harness the full potential of SQL alongside numerous regression algorithms. The integration of machine learning at the database level allows for quicker result retrieval and more effective fraud detection. By abstracting the complexities of data management throughout the machine learning and AI lifecycle, PostgresML permits users to execute machine learning and large language models directly on a PostgreSQL database, making it a robust tool for data-driven decision-making. Ultimately, this innovative approach streamlines processes and fosters a more efficient use of data resources.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Python
Amazon EC2
Codestral Mamba
Falcon
Jupyter Notebook
Llama
Llama 2
Llama 3
Llama 3.1
Llama 3.3
Mathstral
Ministral 3B
Ministral 8B
ORCA
OpenAI
Perl
Postico
PyTorch
Rust
scikit-image

Integrations

Python
Amazon EC2
Codestral Mamba
Falcon
Jupyter Notebook
Llama
Llama 2
Llama 3
Llama 3.1
Llama 3.3
Mathstral
Ministral 3B
Ministral 8B
ORCA
OpenAI
Perl
Postico
PyTorch
Rust
scikit-image

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$.60 per hour
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

CubicWeb

Website

www.cubicweb.org

Vendor Details

Company Name

PostgresML

Website

postgresml.org

Product Features

Product Features

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