The article “MongoDB Vs PostgreSQL: A comparative study on performance aspects”, written by Antonios Makris, Konstantinos Tserpes, Giannis Spiliopoulos, Dimitrios Zissis, Dimosthenis Anagnostopoulos, was originally published electronically on the publisher’s internet portal on 05 June 2020 without open access.

Abstract Several modern day problems need to deal with large amounts of spatio-temporal data. As such, in order to meet the application requirements, more and more systems are adapting to the specificities of those data. The most prominent case is perhaps the data storage systems, that have developed a large number of functionalities to efficiently support spatio-temporal data operations. This work is motivated by the question of which of those data storage systems is better suited to address the needs of industrial applications. In particular, the work conducted, set to identify the most efficient data store system in terms of response times, comparing two of the most representative of the two categories (NoSQL and relational), i.e. MongoDB and PostgreSQL. The evaluation is based upon real, business scenarios and their subsequent queries as well as their underlying infrastructures and concludes in confirming the superiority of PostgreSQL in almost all cases with the exception of the polygon intersection queries. Furthermore, the average response time is radically reduced with the use of indexes, especially in the case of MongoDB.

Compliance to regulatory requirements is a critical concern in information system development projects. Managing this aspect is increasingly challenging while failures impose costly consequence on the organizations world-wide. However, how a legislation may or may not affect information system development projects is often not easily identifiable due to lack of clear understanding and guidelines. This paper presents compliant information system development (CISMET) ontology, exploiting concepts from 21 existing ontologies (regarding regulatory compliance and information system development). The key findings are the six parent classes in the CISMET ontology describing the system development goals, services, process, activities, artifacts, and resources. Also, there are 26 sub classes and 21 class properties that describe various concepts and their relationships in regulatory compliant information system development. The General Data Protection Regulation (GDPR) of the European Union has been instantiated in the proposed framework to indicate how regulatory requirements compliance concepts are mapped to system development projects. Thus, involved stakeholders (information system researchers and system developers) may identify dependencies and actions needed with relation to various rules in the regulation and their link to the system elements through a relevant software application. The latter enables users to easily submit queries towards the backend ontology through a specialized front-end application that can aid in formulating and submitting these queries.

The amount of sources and sheer volumes of spatiotemporal data have met an unprecedented growth during the last decade. As a consequence, a rapidly increasing number of applications are seeking to generate value by crunching those data. The development of a system that will tap into the potential value of the spatiotemporal big data analysis for a multitude of applications remains one of the biggest challenges in computer engineering. This paper delves into the key-characteristics of the most prominent suchlike systems. In particular, it provides a thorough analysis of NoSQL datastores as well as a traditional relational database system in terms of their geospatial querying capabilities.

We present a novel object placement protocol for distributed storage systems that migrates objects between nodes in run time with the goal to minimize the average response times in the system. We rely on a combination of consistent hashing with small lookup tables for objects that have been moved and for which the hash function cannot be aware of. We test our approach in various scenarios based on the assumptions that “get” operations follow a power law distribution and that the request rate is the most significant contributor in the decreasing of the response time based on past research. The results show significant improvements in comparison to the baseline scenario.

This paper presents PORSCE II, a system that combines planning and ontology concept relevance for automatically composing semantic web services. The presented approach includes transformation of the web service composition problem into a planning problem, enhancement with semantic awareness and relaxation and solution through external planners. The produced plans are visualized and their accuracy is assessed.