  The growing popularity of electric vehicles in the United States requires an
ever-expanding infrastructure of commercial DC fast charging stations. The U.S.
Department of Energy estimates 33,355 publicly available DC fast charging
stations as of September 2023. Range anxiety is an important impediment to the
adoption of electric vehicles and is even more relevant in underserved regions
in the country. The peer-to-peer energy marketplace helps fill the demand by
allowing private home and small business owners to rent their 240 Volt, level-2
charging facilities. The existing, publicly accessible outlets are wrapped with
a Cloud-connected microcontroller managing security and charging sessions.
These microcontrollers act as Edge devices communicating with a Cloud message
broker, while both buyer and seller users interact with the framework via a
web-based user interface. The database storage used by the marketplace
framework is a key component in both the cost of development and the
performance that contributes to the user experience. A traditional storage
solution is the SQL database. However, difficulty in scaling across multiple
nodes and cost of its server-based compute have resulted in a trend in the last
20 years towards other NoSQL, serverless approaches. In this study, we evaluate
the NoSQL vs. SQL solutions through a comparison of Google Cloud Firestore and
Cloud SQL MySQL offerings. The comparison pits Google's serverless,
document-model, non-relational, NoSQL against the server-base, table-model,
relational, SQL service. The evaluation is based on query latency,
flexibility/scalability, and cost criteria. Through benchmarking and analysis
of the architecture, we determine whether Firestore can support the energy
marketplace storage needs and if the introduction of a GraphQL middleware layer
can overcome its deficiencies.
