The world is becoming more and more digitized which in turn puts pressure on existing applications and systems to be able to handle large quantities of data. And  in some cases, that data also needs to be operated in secure and isolated environments. To address these needs, a new category  of databases has emerged, by the name of NewSQL. The downside of this new category is that it still remains unexplored in some areas, such as how each database under that category performs towards each other, or even towards databases belonging to other categories. One major aspect, in terms of performance is latency, since it affects the overall user-experience. In order to clear up some of the unexplored areas within NewSQL, two databases were studied in the context of their latency performance: CockroachDB and Vitess. The study was divided into two main parts. The first one, was a quantitative study, which was about gathering data on how each database performed in terms of latency when serving the create, read, update, and delete-operations. No clear differences in latency were found for the create- and read-operations. While the results for update- and delete-operations showed significant differences where Vitess had lower latency than CockroachDB.  The second part of this study was a qualitative study, dedicated to analyze and inspect each database architecture and source code. The intention was to identify potential factors that may affect latency performance. The outcome from the analysis was that three main factors could be identified. The first identified factor is that CockroachDB had a layered architecture and that it needed to translate SQL queries into a set of key-value operations. The second one is that the databases makes use of different storage engines, which in turn can have differences in performance. The third and final identified factor is that MySQL, which was integrated with Vitess, had existed for a longer period of time compared to CockroachDB. Which indicates that the database probably has been more optimized over the years.