Oracle Spatial and Graph 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.
Oracle Spatial and Graph Alternatives
ManageEngine EventLog Analyzer
EventLog Analyzer from Manage Engine is the industry's most affordable security information and event management software (SIEM). This cloud-based, secure solution provides all essential SIEM capabilities, including log analysis, log consolidation, user activity monitoring and file integrity monitoring. It also supports event correlation, log log forensics and log retention. Real-time alerting is possible with this powerful and secure solution. Manage Engine's EventLog Analyzer allows users to prevent data breaches, detect the root cause of security issues, and mitigate sophisticated cyber-attacks.
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DataHub
DataHub is a versatile open-source metadata platform crafted to enhance data discovery, observability, and governance within various data environments. It empowers organizations to easily find reliable data, providing customized experiences for users while avoiding disruptions through precise lineage tracking at both the cross-platform and column levels. By offering a holistic view of business, operational, and technical contexts, DataHub instills trust in your data repository. The platform features automated data quality assessments along with AI-driven anomaly detection, alerting teams to emerging issues and consolidating incident management. With comprehensive lineage information, documentation, and ownership details, DataHub streamlines the resolution of problems. Furthermore, it automates governance processes by classifying evolving assets, significantly reducing manual effort with GenAI documentation, AI-based classification, and intelligent propagation mechanisms. Additionally, DataHub's flexible architecture accommodates more than 70 native integrations, making it a robust choice for organizations seeking to optimize their data ecosystems. This makes it an invaluable tool for any organization looking to enhance their data management capabilities.
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InfiniteGraph
InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise.
InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database.
InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest.
InfiniteGraph has client-side caching which caches frequently used node and edges. This can allow InfiniteGraph to perform like an in-memory graph database.
InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other graph databases.
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PuppyGraph
PuppyGraph allows you to effortlessly query one or multiple data sources through a cohesive graph model. Traditional graph databases can be costly, require extensive setup time, and necessitate a specialized team to maintain. They often take hours to execute multi-hop queries and encounter difficulties when managing datasets larger than 100GB. Having a separate graph database can complicate your overall architecture due to fragile ETL processes, ultimately leading to increased total cost of ownership (TCO). With PuppyGraph, you can connect to any data source, regardless of its location, enabling cross-cloud and cross-region graph analytics without the need for intricate ETLs or data duplication. By directly linking to your data warehouses and lakes, PuppyGraph allows you to query your data as a graph without the burden of constructing and maintaining lengthy ETL pipelines typical of conventional graph database configurations. There's no longer a need to deal with delays in data access or unreliable ETL operations. Additionally, PuppyGraph resolves scalability challenges associated with graphs by decoupling computation from storage, allowing for more efficient data handling. This innovative approach not only enhances performance but also simplifies your data management strategy.
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Integrations
Company Details
Company:
Oracle
Year Founded:
1977
Headquarters:
United States
Website:
www.oracle.com/database/graph/
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Product Details
Platforms
Web-Based
Windows
Types of Training
Training Docs
Training Videos
Customer Support
Business Hours
Online Support
Oracle Spatial and Graph Features and Options
GIS Software
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
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