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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 Oracle Analytics Server?

Oracle Analytics Server is a sophisticated tool designed to empower business analysts and decision-makers in uncovering critical insights and facilitating faster, informed choices. This platform brings the advanced features of Oracle Analytics Cloud to organizations that require on-premises solutions. By adopting Oracle Analytics Server, businesses gain the advantage of augmented analytics along with superior data discovery capabilities, all while addressing their specific configuration needs. This flexibility is particularly beneficial for companies facing strict regulatory requirements or those utilizing multi-cloud environments, as they can access top-tier analytical tools tailored to their deployment preferences. Furthermore, Oracle Analytics Server guarantees that legacy systems remain functional and offers a seamless pathway to transition to Oracle Cloud at their convenience. In addition, the platform features sophisticated, AI-enhanced self-service analytics that streamline data preparation, significantly improving user experience. Ultimately, Oracle Analytics Server positions organizations to harness the power of data more effectively than ever before.

Media

Media

Integrations Supported

Oracle Analytics Cloud
QGIS
TransCAD

Integrations Supported

Oracle Analytics Cloud
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

Oracle

Date Founded

1977

Company Location

United States

Company Website

docs.oracle.com/en/middleware/bi/analytics-server/user-oas/oracle-analytics-server.html

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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