Oracle international corporation (20240126764). EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE simplified abstract

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 20240126764 titled 'EFFICIENT COMPILATION OF BOUNDED RECURSIVE GRAPH QUERIES ON TOP OF SQL BASED RELATIONAL ENGINE

Simplified Explanation

The techniques described in the patent application support graph pattern matching queries inside a relational database management system (RDBMS) that supports SQL execution. These techniques compile a graph pattern matching query, including a bounded recursive pattern query, into an SQL query that can be executed by the relational engine without any changes to the existing SQL engine. This enables the execution of graph pattern matching queries with bounded recursive patterns on top of the relational engine.

• Enables graph pattern matching queries within an RDBMS supporting SQL execution.
• Compiles graph pattern matching queries with bounded recursive patterns into SQL queries.
• Allows execution of graph pattern matching queries without altering the existing SQL engine.

Potential Applications

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

Problems Solved

1. Efficiently executing graph pattern matching queries within an RDBMS. 2. Enabling bounded recursive pattern queries without changing the SQL engine.

Benefits

1. Improved performance in executing complex graph pattern matching queries. 2. Seamless integration with existing relational database systems. 3. Enhanced capabilities for analyzing interconnected data.

Potential Commercial Applications

Optimizing data processing in industries such as finance, healthcare, e-commerce, and telecommunications.

Possible Prior Art

One possible prior art could be the use of graph databases for handling graph pattern matching queries, but the innovation here lies in enabling these queries within an RDBMS without modifying the SQL engine.

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

The article does not provide a direct comparison between this technology and existing graph database solutions. It would be helpful to understand the specific advantages or limitations of this approach compared to traditional graph databases.

What are the potential limitations or constraints of implementing bounded recursive pattern queries in an RDBMS environment?

The article does not delve into the potential challenges or constraints that may arise when implementing bounded recursive pattern queries within an RDBMS. It would be beneficial to explore any performance implications or scalability issues that could arise in practice.

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.