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Description

Apache TinkerPop™ serves as a framework for graph computing, catering to both online transaction processing (OLTP) with graph databases and online analytical processing (OLAP) through graph analytic systems. The traversal language utilized within Apache TinkerPop is known as Gremlin, which is a functional, data-flow language designed to allow users to effectively articulate intricate traversals or queries related to their application's property graph. Each traversal in Gremlin consists of a series of steps that can be nested. In graph theory, a graph is defined as a collection of vertices and edges. Both these components can possess multiple key/value pairs referred to as properties. Vertices represent distinct entities, which may include individuals, locations, or events, while edges signify the connections among these vertices. For example, one individual might have connections to another, have participated in a certain event, or have been at a specific location recently. This framework is particularly useful when a user's domain encompasses a diverse array of objects that can be interconnected in various ways. Moreover, the versatility of Gremlin enhances the ability to navigate complex relationships within the graph structure seamlessly.

Description

GraphAware presents Hume, an innovative platform for data analytics and intelligence analysis that leverages graph technology to convert isolated structured and unstructured data into a cohesive web, enhancing insight and decision-making capabilities. Central to Hume's functionality are the principles of knowledge graphs and graph databases, which allow for the seamless ingestion, unification, and representation of data as interconnected networks of nodes and relationships, empowering analysts and data scientists to explore, query, and visualize complex connections and concealed patterns without the necessity of mastering intricate query languages. This platform provides a unified perspective of truth across various data sources, speeds up the identification of subtle relationships and behavioral patterns, and facilitates advanced graph data science techniques such as node influence analysis, link prediction, community detection, and automated alerting, all bolstered by integrated machine learning and features from large language models (LLMs). By streamlining the access and analysis of diverse data sets, Hume not only enhances the efficiency of data exploration but also opens up new avenues for strategic decision-making.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Groovy
Docker
G.V() Gremlin IDE
Java
Node.js
Python

Integrations

Apache Groovy
Docker
G.V() Gremlin IDE
Java
Node.js
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

Apache Software Foundation

Country

United States

Website

tinkerpop.apache.org

Vendor Details

Company Name

GraphAware

Founded

2013

Country

United Kingdom

Website

graphaware.com

Product Features

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

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