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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 AllegroGraph?

AllegroGraph stands out as a groundbreaking solution that facilitates limitless data integration, employing a proprietary method to consolidate fragmented data and information into an Entity Event Knowledge Graph framework designed for extensive big data analysis. By leveraging its distinctive federated sharding features, AllegroGraph delivers comprehensive insights and supports intricate reasoning over a distributed Knowledge Graph. Additionally, users of AllegroGraph can access an integrated version of Gruff, an intuitive browser-based tool for graph visualization that aids in uncovering and understanding relationships within enterprise Knowledge Graphs. Moreover, Franz's Knowledge Graph Solution not only encompasses advanced technology but also offers services aimed at constructing robust Entity Event Knowledge Graphs, drawing upon top-tier products, tools, expertise, and experience in the field. This comprehensive approach ensures that organizations can effectively harness their data for strategic decision-making and innovation.

Media

Media

Integrations Supported

Apache Solr
Cloudera
Docker
Hackolade
Kubernetes
MongoDB
PoolParty
QGIS
Swarm
TransCAD

Integrations Supported

Apache Solr
Cloudera
Docker
Hackolade
Kubernetes
MongoDB
PoolParty
QGIS
Swarm
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

Franz Inc.

Company Location

San Francisco Bay Area

Company Website

www.franz.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 Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Knowledge Management

Artificial Intelligence (AI)
Cataloging / Categorization
Collaboration
Content Management
Decision Tree
Discussion Boards
Full Text Search
Knowledge Base Management
Self Service Portal

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

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