In 2019, a new ISO standard for a Property Graph Database query language was approved. A working group is actively developing this new language, called GQL. It draws inspiration from existing languages developed by independent vendors and communities, expressing queries with the help of graph patterns. Graph pattern matching will become a field of interest in order to efficiently evaluate these queries that are highly dependent on the connectivity of data. An algorithm is proposed in order to evaluate these graph patterns, which makes use of an intermediate tree structure to build the result set. A comparison of runtime of the algorithm is carried out, with different variations of the algorithm that start the evaluation of the path patterns...
In the past decade Knowledge graphs have become very popular and frequently rely on the Resource Des...
Graph databases with a custom non-relational backend promote themselves to outperform relational dat...
An important step in data analysis is the exploration of data. For traditional relational databases ...
The development of practical query languages for graph databases runs well ahead of the underlying t...
Compared to relational databases, graph database systems provide a novel way of processing and analy...
As graph databases become widespread, JTC1 -- the committee in joint charge of information technolog...
In the past decade, property graph databases have emerged as a growing niche in data management. Ma...
Regular Path Queries (RPQs) are at the core of many recent declarative graph pattern matching langua...
We introduce a framework for cardinality estimation of query patterns over property graph databases....
The growing popularity of graph databases has generated interesting data management problems, such a...
Graph querying and pattern matching is becoming an important feature of graph processing as it allow...
International audienceGQL (Graph Query Language) is being developed as a new ISO standard for graph ...
In property graph query languages, nothing other than the properties of the current edge and those o...
Abstract—It is increasingly common to find graphs in which edges bear different types, indicating a ...
Graph data management has revealed beneficial characteristics in terms of flexibility and scalabilit...
In the past decade Knowledge graphs have become very popular and frequently rely on the Resource Des...
Graph databases with a custom non-relational backend promote themselves to outperform relational dat...
An important step in data analysis is the exploration of data. For traditional relational databases ...
The development of practical query languages for graph databases runs well ahead of the underlying t...
Compared to relational databases, graph database systems provide a novel way of processing and analy...
As graph databases become widespread, JTC1 -- the committee in joint charge of information technolog...
In the past decade, property graph databases have emerged as a growing niche in data management. Ma...
Regular Path Queries (RPQs) are at the core of many recent declarative graph pattern matching langua...
We introduce a framework for cardinality estimation of query patterns over property graph databases....
The growing popularity of graph databases has generated interesting data management problems, such a...
Graph querying and pattern matching is becoming an important feature of graph processing as it allow...
International audienceGQL (Graph Query Language) is being developed as a new ISO standard for graph ...
In property graph query languages, nothing other than the properties of the current edge and those o...
Abstract—It is increasingly common to find graphs in which edges bear different types, indicating a ...
Graph data management has revealed beneficial characteristics in terms of flexibility and scalabilit...
In the past decade Knowledge graphs have become very popular and frequently rely on the Resource Des...
Graph databases with a custom non-relational backend promote themselves to outperform relational dat...
An important step in data analysis is the exploration of data. For traditional relational databases ...