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What is Oracle Spatial and Graph?

Graph databases, an essential component of Oracle's converged database offering, eliminate the need for creating a separate database and migrating data. This innovation empowers analysts and developers in the banking industry to perform fraud detection, reveal connections and relationships within data, and improve traceability in smart manufacturing, all while enjoying the advantages of enterprise-grade security, seamless data ingestion, and strong support for diverse data workloads. The Oracle Autonomous Database features Graph Studio, which provides a one-click setup, integrated tools, and enhanced security protocols. Graph Studio simplifies the oversight of graph data and supports the modeling, analysis, and visualization throughout the entirety of the graph analytics process. Oracle accommodates both property and RDF knowledge graphs, facilitating the representation of relational data as graph structures. Furthermore, users can execute interactive graph queries directly on the graph data or through a high-performance in-memory graph server, allowing for effective data processing and analysis. This incorporation of graph technology not only augments the capabilities of data management within Oracle's ecosystem but also enhances the overall efficiency of data-driven decision-making processes. Ultimately, the combination of these features positions Oracle as a leader in the realm of advanced data management solutions.

What is GraphAware?

GraphAware introduces Hume, a cutting-edge platform designed for data analytics and intelligence evaluation, which utilizes graph technology to transform disparate structured and unstructured data into an integrated web, thereby improving insight and decision-making processes. At the heart of Hume’s capabilities are knowledge graphs and graph databases, which enable the smooth ingestion, unification, and visualization of data as interconnected networks of nodes and their relationships, allowing analysts and data scientists to investigate, query, and reveal intricate connections and hidden trends without needing to learn complex query languages. This platform offers a comprehensive view of truth derived from multiple data sources, accelerates the discovery of nuanced relationships and behavioral trends, and supports advanced graph data science methods like node influence analysis, link prediction, community detection, and automated alerts, all enhanced by incorporated machine learning and features from extensive language models. By simplifying the access and examination of varied data sets, Hume not only boosts the efficiency of data exploration but also creates new possibilities for informed strategic decision-making. As a result, organizations can leverage Hume to gain a competitive edge in their analytical pursuits.

Media

Media

Integrations Supported

QGIS
TransCAD

Integrations Supported

QGIS
TransCAD

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

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/database/graph/

Company Facts

Organization Name

GraphAware

Date Founded

2013

Company Location

United Kingdom

Company Website

graphaware.com

Categories and Features

GIS

3D Imagery
Census Data Integration
Color Coding
Geocoding
Image Exporting
Image Management
Internet Mapping
Interoperability
Labeling
Map Creation
Map Sharing
Near-Matching
Reverse Geocoding
Spatial Analysis

Categories and Features

Data Analysis

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

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