Nebula Graph vs. OpenNebula vs. Oracle Spatial and Graph vs. Python Comparison Chart

The graph database built for super large-scale graphs with milliseconds of latency. We are continuing to collaborate with the community to prepare, popularize and promote the graph database. Nebula Graph only allows authenticated access via role-based access control. Nebula Graph supports multiple storage engine types and the query language can be extended to support new algorithms. Nebula Graph provides low latency read and write , while still maintaining high throughput to simplify the most complex data sets. With a shared-nothing distributed architecture , Nebula Graph offers linear scalability. Nebula Graph's SQL-like query language is easy to understand and powerful enough to meet complex business needs. With horizontal scalability and a snapshot feature, Nebula Graph guarantees high availability even in case of failures. Large Internet companies like JD, Meituan, and Xiaohongshu have deployed Nebula Graph in production environments.

Graph databases, part of Oracle’s converged database offering, eliminate the need to set up a separate database and move data. Analysts and developers can perform fraud detection in banking, find connections and link to data, and improve traceability in smart manufacturing, all while gaining enterprise-grade security, ease of data ingestion, and strong support for data workloads. Oracle Autonomous Database includes Graph Studio, with one-click provisioning, integrated tooling, and security. Graph Studio automates graph data management and simplifies modeling, analysis, and visualization across the graph analytics lifecycle. Oracle provides support for both property and RDF knowledge graphs, and simplifies the process of modeling relational data as graph structures. Interactive graph queries can run directly on graph data or in a high-performance in-memory graph server.