This dissertation explores the many aspects of NoSQL databases, with an emphasis on two key principles. First, we'll discuss NoSQL database benchmarking, an essential step toward selecting the right system for particular requirements. And then focused on leveraging NoSQL database capabilities to enhance performance in practical applications. In this dissertation, we will discuss the importance of benchmarking, the methods used to conduct benchmarks, and the most used benchmarking software. Then, compare Redis and HBase, two popular key-value NoSQL databases, using the Yahoo Cloud Service Benchmarking Tool (YCSB). And take a look at how they were rated on the job.

In addition, the dissertation will provide a trip planning algorithm (one that can determine the best routes between two specified points) and provide an overview of GTFS data. Then, present the strategy of employing the Redis NoSQL database to accelerate the process of discovering a trip plan utilising GTFS data.

Discovering potential routes and verifying them in light of the trip's schedule are the two main components of the trip planning process. An algorithm for validating trips in accordance with the trip schedule will be presented in the dissertation. The Range Mapping Hash is a Redis structure that was designed to speed up the trip time verifying process; it is another example of the use of a NoSQL database.

In the dissertation, the performance of both trip planning and trip time validation are measured and compared with and without the proposed method of utilizing NoSQL database.

One of the problems with the most widely used benchmarking tools and methods today is that they do not account for the specifics of the benchmarking application. Using the GTFS trip planner application as an example, this paper will introduce the method of benchmarking the database based on application interaction. In this section, we will compare Redis and MongoDB as storage for GTFS databases.