Advanced technologies in location acquisition allow us to track the movement of moving objects (people, planes, vehicles, animals, ships, ...) in geographical space. These technologies generate a vast amount of trajectory data (TD). Several applications in different fields can utilize such TD, for example, traffic management control, social behavior analysis, wildlife migrations and movements, ship trajectories, shoppers behavior in a mall, facial nerve trajectory, location-based services and many others. Trajectory data can be mainly handled either with Moving Object Databases (MOD) or Trajectory Data Warehouse (TDW). In this paper, we aim to review existing studies on storing, managing, and analyzing TD using data warehouse technologies. We propose a framework that aims to provide the requirements for building the TDW. Furthermore, we discuss different applications using the TDW and how these applications utilize the TDW. We address some issues with existing TDWs and discuss future work in this field.

Database code fragments exist in software systems by using Structured Query Language (SQL) as the standard language for relational databases. Traditionally, developers bind databases as backends to software systems for supporting user applications. However, these bindings are low‐level code and implemented to persist user data, so Object Relational Mapping (ORM) frameworks take place to abstract database access details. Both approaches are prone to problematic database code fragments that negatively impact the quality of software systems. We survey problematic database code fragments in the literature and examine antipatterns that occur in low‐level database access code using SQL and high‐level counterparts ORM frameworks. We also study problematic database code fragments in different and popular software architectures such as Service‐Oriented Architecture, Microservice Architecture, and Model View Controller. We create a novel categorization of both SQL schema and query antipatterns in terms of performance, maintainability, portability, and data integrity.

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