17965687. EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE simplified abstract (Oracle International Corporation)

EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE

Organization Name

Oracle International Corporation

Inventor(s)

VLAD IOAN Haprian of Zurich (CH)

LEI Sheng of Foster City CA (US)

LAURENT Daynes of Saint-Ismier (FR)

ZHEN HUA Liu of San Mateo CA (US)

HUGO Kapp of Zurich (CH)

MARCO Arnaboldi of Zurich (CH)

ANDREW Witkowski of Foster City CA (US)

SUNGPACK Hong of Palo Alto CA (US)

HASSAN Chafi of San Mateo CA (US)

EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE - A simplified explanation of the abstract

This abstract first appeared for US patent application 17965687 titled 'EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE

Simplified Explanation

The techniques described in the patent application enable the execution of graph pattern matching queries, including bounded recursive patterns, within a relational database management system that supports SQL execution. By compiling the graph pattern matching query into a SQL query that can be executed by the relational engine, these techniques allow for the execution of complex graph pattern matching queries without requiring any changes to the existing SQL engine.

• Techniques support graph pattern matching queries inside an RDBMS
• Techniques compile graph pattern matching queries into SQL queries
• Enables execution of graph pattern matching queries with bounded recursive patterns
• Does not require changes to existing SQL engine

Potential Applications

The technology could be applied in various fields such as data analytics, network analysis, social media analysis, and recommendation systems.

Problems Solved

1. Efficiently executing graph pattern matching queries within an RDBMS 2. Handling complex graph patterns, including bounded recursive patterns, in SQL queries

Benefits

1. Improved performance and efficiency in executing graph pattern matching queries 2. Seamless integration with existing relational database systems 3. Ability to handle complex graph patterns without changing the SQL engine

Potential Commercial Applications

Optimizing database queries, data mining, fraud detection, and pattern recognition in various industries such as finance, healthcare, and e-commerce.

Possible Prior Art

One possible prior art could be the use of graph databases for handling graph pattern matching queries, which may not be as efficient or integrated with relational database systems as the techniques described in the patent application.

How does this technology compare to existing graph database systems for handling graph pattern matching queries?

The article does not provide a direct comparison between this technology and existing graph database systems in terms of performance, efficiency, and integration with relational database systems.

What are the potential limitations or drawbacks of implementing these techniques in a real-world scenario?

The article does not address any potential limitations or drawbacks that may arise when implementing these techniques in a real-world scenario, such as scalability issues or compatibility with different database systems.

Original Abstract Submitted

Techniques support graph pattern matching queries inside a relational database management system (RDBMS) that supports SQL execution. The techniques compile a graph pattern matching query that includes a bounded recursive pattern query into a SQL query that can then be executed by the relational engine. As a result, techniques enable execution of graph pattern matching queries that include bounded recursive patterns on top of the relational engine by avoiding any change in the existing SQL engine.