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ease
features
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support

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Description

AnzoGraph DB boasts an extensive array of analytical features that can significantly improve your analytical framework. Check out this video to discover how AnzoGraph DB operates as a Massively Parallel Processing (MPP) native graph database specifically designed for data harmonization and analytics. This horizontally scalable graph database is optimized for online analytics and tackling data harmonization issues. Addressing challenges related to linked data, AnzoGraph DB stands out as a leading analytical graph database in the market. It offers robust online performance suitable for enterprise-scale graph applications, ensuring efficiency and speed. AnzoGraph DB employs familiar SPARQL*/OWL for semantic graphs, while also accommodating Labeled Property Graphs (LPGs). Its vast array of analytical, machine learning, and data science tools empowers users to uncover new insights at remarkable speed and scale. By prioritizing context and relationships among data, you can enhance your analysis significantly. Additionally, the database enables ultra-fast data loading and execution of analytical queries, making it an invaluable asset for any data-driven organization.

Description

Graph databases, which are a key feature of Oracle's converged database solution, remove the necessity for establishing a distinct database and transferring data. This allows analysts and developers to conduct fraud detection in the banking sector, uncover relationships and links to data, and enhance traceability in smart manufacturing, all while benefiting from enterprise-level security, straightforward data ingestion, and robust support for various data workloads. The Oracle Autonomous Database incorporates Graph Studio, offering one-click setup, built-in tools, and advanced security measures. Graph Studio streamlines the management of graph data and facilitates the modeling, analysis, and visualization throughout the entire graph analytics lifecycle. Oracle supports both property and RDF knowledge graphs, making it easier to model relational data as graph structures. Additionally, interactive graph queries can be executed directly on the graph data or via a high-performance in-memory graph server, enabling efficient data processing and analysis. This integration of graph technology enhances the overall capabilities of data management within Oracle's ecosystem.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
QGIS
Red Hat Cloud Suite
Tableau
TransCAD

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
QGIS
Red Hat Cloud Suite
Tableau
TransCAD

Pricing Details

No price information available.
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

Cambridge Semantics

Founded

2007

Country

United States

Website

www.cambridgesemantics.com/anzograph/

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/database/graph/

Product Features

Product 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

Alternatives

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GraphDB

Ontotext

Alternatives

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FactNexus
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GraphBase

FactNexus
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InfiniteGraph

Objectivity