• Corpus ID: 14193807

Graph or Relational Databases: A Speed Comparison for Process Mining Algorithm

  title={Graph or Relational Databases: A Speed Comparison for Process Mining Algorithm},
  author={Jeevan Joishi and Ashish Sureka},
Process-Aware Information System (PAIS) are IT systems that manages, supports business processes and generate large event logs from execution of business processes. [] Key Method We implement Similar-Task and Sub-Contract algorithms on relational and NoSQL (graph-oriented) databases using only query language constructs. We conduct empirical analysis on a large real world data set to compare the performance of row-oriented database and NoSQL graph-oriented database. We benchmark performance factors like query…

Graph-based process mining

This paper introduces and formalizes a new approach to store and retrieve event logs into/from graph databases by defining an algorithm to compute Directly Follows Graph (DFG) inside the graphdatabase, which shifts the heavy computation parts of process mining into the graph database.

Graph-Based Algorithms for Discovering a Process Model Containing Invisible Tasks

This research proposes a graph-based algorithm to mine the data from an event log and establishes an additional-invisible-task process model by converting all of the processes in the event log into a link list and adding invisible tasks and operators for parallel relations, such as XOR Split or XOR Join.

The Suitability of Graph Databases for Big Data Analysis: A Benchmark

This paper designs and performs tests that examine where are the borders for specific query types in Big Data scenarios concerning the query and works with Neo4j and PostgreSQL as a representative of graph databases and non-graph databases.


A processing performance of semi-structured geospatial data in different databases management systems (DBMS) is analyzed and the conclusions can be used to support content-based estimations of the demands to the DBMS and its restrictions at the database design stage.

Graph-based Process Discovery containing Invisible Non-Prime Task in Procurement of Animal-Based Ingredient of Halal Restaurants

A graph-based process discovery algorithm is proposed to form a process model containing invisible non-prime tasks based on the procurement processes to help halal level examiners check halal implementation based on Halal Critical Control Points.

A New Similarity Method based on Weighted-Linear Temporal Logic Tree and Weighted Directed Acyclic Graph for Graph-based Business Process Models

A new similarity method is proposed that combines Weighted-Linear Temporal Logic (W-LTL) Tree and Weighted Directed Acyclic Graph (wDAG) that modifies the original wD AG similarity, so it can distinguish the similarity value of two wDAGs that have two branches with opposite weight values.

About the Fairness of Database Performance Comparisons

This paper invalidates some stated results about the bad performance of relational systems in those scenarios that are commonly used in comparisons and presents some general considerations how fairness of comparisons can be improved.

Discovering care pathways for multi-morbid patients using event graphs

This work explored the potential of analyzing clinical pathways of multi-morbid patients using an event log representation reflecting the independent clinical processes and showed that paths involving multiple entities include traditional process mining concepts not for one clinical process but all involved processes.

Data Management Technologies and Applications: 8th International Conference, DATA 2019, Prague, Czech Republic, July 26–28, 2019, Revised Selected Papers

Besides providing further details about the developed C3 TFIDF-SVM classifier, the classifiers effectiveness for different text categorization problems spanning two natural languages is investigated and the generated explanation understandability is investigated.

Database Performance Comparisons: An Inspection of Fairness

This paper revisit certain statements about comparisons between the Neo4j graph database and relational systems and indicate a couple of possible reasons for coming up with bad performance such as inappropriate or default configurations, and too straightforward implementations.



Vishleshan: Performance Comparison and Programming Process Mining Algorithms in Graph-Oriented and Relational Database Query Languages

This work implements Similar-Task algorithm on relational and NoSQL (graph oriented) databases using only query language constructs and conducts empirical analysis on a large real world data set to investigate which of the databases perform better for Organizational Mining under Process Mining.

Khanan: Performance Comparison and Programming \alpha α -Miner Algorithm in Column-Oriented and Relational Database Query Languages

A performance benchmarking and comparison of the α-miner algorithm on row- oriented database and NoSQL column-oriented database and a comparison on various aspects like time taken to load large datasets, disk usage, stepwise execution time and compression technique are presented.

Pragamana: Performance Comparison and Programming Alpha-miner Algorithm in Relational Database Query Language and NoSQL Column-Oriented Using Apache Phoenix

A performance benchmarking and comparison of the α-miner algorithm on row- oriented database and NoSQL column-oriented database so that they can compare which database can efficiently store massive event logs and analyze it in seconds to discover a process model.

Discovering Social Networks from Event Logs

This paper defines metrics, presents a tool, and applies these to a real event log within the setting of a large Dutch organization, to build a social network based on the hand-over of work from one performer to the next.

Utility-Based Control Flow Discovery from Business Process Event Logs

The focus of the work presented in this paper is to incorporate the statistical based on frequency and semantic based on user's objective aspects while driving a process model using a Utility-Based Fuzzy Miner UBFM algorithm.

Workflow mining: discovering process models from event logs

A new algorithm is presented to extract a process model from a so-called "workflow log" containing information about the workflow process as it is actually being executed and represent it in terms of a Petri net.

A comparison of a graph database and a relational database: a data provenance perspective

This paper reports on a comparison of one such NoSQL graph database called Neo4j with a common relational database system, MySQL, for use as the underlying technology in the development of a software system to record and query data provenance information.

GraphMiner: a structural pattern-mining system for large disk-based graph databases and its applications

A demo of GraphMiner is described which showcases the technical details of the index structure and the mining algorithms including their efficient implementation, the mining performance and the comparison with some state-of-the-art methods.

Scalable mining of large disk-based graph databases

An effective index structure, ADI (for adjacency index), is developed to support mining various graph patterns over large databases that cannot be held into main memory and is faster than gSpan when both can run in main memory.