## 2 Related Work  
Researchers have extensively examined the performance differences between relational and NoSQL databases, exploring both their overall capabilities and their suitability for various application domains. In our search, we used as keywords \"performance\", \"Neo4j\", \"graph database\", \"relational database\", \"concurrent access\", \"complex queries\", \"comparison\", \"NoSQL\", \"navigation\", and \"Dijkstra\", which we considered in relation with to our research, combined using Boolean operators like \"AND\" and \"OR\". Studies have shown that traditional relational databases face challenges in handling high-concurrency workloads, particularly with complex transactions. For instance, [PERSON] and [PERSON] [PERSON] and [PERSON] (2018) discussed the fundamental principles of relational database management systems and highlighted performance bottlenecks associated with traditional locking mechanisms during concurrent access, which can lead to reduced throughput and increased latency in multi-user environments. In contrast, the emergence of NoSQL databases, particularly graph databases, has prompted investigations into their ability to manage complex queries efficiently. [PERSON] and [PERSON] [PERSON] and [PERSON] (2018) presented a comprehensive overview of graph database models, noting their advantages in traversing relationships efficiently, which can significantly outperform relational databases for certain query types. Their work laid the foundation for understanding how graph databases handle concurrent access compared to their relational counterparts. [PERSON] (2018) conducted a systematic literature review on database management system (DBMS) performance comparisons, compiling and analyzing existing research to provide a comprehensive overview of the field. This review aimed to assess how different DBMSs, including both relational and NoSQL systems, have been evaluated in terms of performance. By systematically examining past studies, the authors sought to identify common methodologies, benchmarks, and metrics used to compare databases. Another literature review, [8], highlighted the strength of the NoSQL databases and how they set them apart from the rigid relational ones through their flexible structure, but also their weaknesses, concluded that they are not a replacement for SQL databases. Several researchers have conducted performance analyses comparing NoSQL databases with traditional relational databases, particularly focusing on their effectiveness for application data storage [9]. The paper [10] compared SQL databases with NoSQL graph databases, particularly in the context of physical database tuning techniques. In these studies, SQL databases, which rely on structured schemas and relational models, are analyzed for how tuning methods--such as indexing, partitioning, and query optimization--affect performance. These physical tuning techniques are crucial for improving efficiency in handling complex queries and large datasets. In contrast, NoSQL graph databases, like Neoij, excel in managing and querying highly interconnected data, such as social networks or recommendation systems. Other scientific papers have explored the performance of graph and relational databases when handling complex queries, providing valuable insights into their comparative strengths and weaknesses [11]. The authors of [12] wrote a technical report presenting a comprehensive comparison between graph databases, like Neoij, and relational databases, such as MySQL, focusing on their performance across various types of queries. These studies emphasize the structural differences between the two, with Neoij utilizing graph structures--nodes, edges, and properties--to represent data, while MySQL relies on tables and defined relationships. The research [13] focused on the architecture and performance characteristics of graph databases under concurrent workloads. Their findings suggest that graph databases like Neoij outperform relational databases in scenarios involving complex, highly interconnected datasets.