Oracle is pleased to be recognized as a Leader in The Forrester Wave™: Graph Data Platforms, Q4 2020. Oracle scored 5 out of 5 for graph data platforms in ten criteria:
The report noted, “Oracle supports both RDF (Resource Description Framework) and property graph models,” and observed that, “Customers like Oracle’s capabilities for technical support, PGQL, ease to start with SQL-like syntax and performance for moderately sized deployments.”
Oracle has a unique approach to graph platforms by offering graphs and analytics in a converged database—a single platform for multiple data types and models as well as multiple workloads: operational, transactional, analytic and more—with Oracle Database on premises, in Oracle Cloud Infrastructure (OCI), on Exadata Cloud@Customer, and in Oracle Autonomous Database.
With a converged database, analysts and developers can seamlessly perform graph analysis on data used in other systems, like data warehouses or transaction systems. They can also transparently use in-memory and partitioning features to enhance query performance and scalability. Or combine social network analysis with location analysis to understand how social network communities and influencers may be related to where people and places are in the real world, and use the results of graph analysis as “signal input” for AI and machine learning applications.
Oracle’s property graph features offer powerful analytics and fast, enterprise-grade performance to help discover insights so that organizations become more data-driven. Developers and analysts can perform common graph queries and analyses with nearly 60 high-performance graph algorithms, including pattern matching, detecting cycles, finding important nodes, community detection, and recommendations using Java, Python and PGQL, a native SQL-like query language.
Property graphs can also be used to discover fraud, perform customer-360 analysis, understand dependencies in manufacturing and networks, and perform social network and relationship analysis.
RDF graph features provide a high performance, scalable, standards-compliant RDF database with native inferencing, just-in-time reasoning, ontology support, and the ability to scale to trillions of triples. With support for all datatypes and enterprise database capabilities, it is widely used for linked data, data integration, and knowledge graphs by statistics agencies, pharmaceutical companies, and publication offices.
Oracle also offers enterprise graph scalability and performance. The deployment at the National Statistics Center, Japan, shows how well graph queries scale through a massive enterprise graph representing all census and statistical data published by the Japanese government and accessed by government agencies, businesses, and the public. Their graph grew from 1.1 billion triples to 2.1 billion triples in a year and the average graph query performance was a consistent 1.27 seconds.
Because Oracle provides a common, converged platform for all enterprise data, data can be modeled as graphs and graph analysis can be performed on the same powerful data management platform used to manage all your operations. As a result, graph applications can use the industry-leading ETL, data preparation, replication, and streaming and enterprise data management capabilities that have made Oracle the world’s converged database leader. Oracle has invested heavily to simplify and automate complex data management tasks to:
As part of Oracle’s commitment to innovation, you can not only create and work with graphs, but also apply graph analysis to the systems, processes, and data you work with every day.