  In recent years, the increased need to house and process large volumes of
data has prompted the need for distributed storage and querying systems. The
growth of machine-readable RDF triples has prompted both industry and academia
to develop new database systems, called NoSQL, with characteristics that differ
from classical databases. Many of these systems compromise ACID properties for
increased horizontal scalability and data availability. This thesis concerns
the development and evaluation of a NoSQL triplestore. Triplestores are
database management systems central to emerging technologies such as the
Semantic Web and linked data. The evaluation spans several benchmarks,
including the two most commonly used in triplestore evaluation, the Berlin
SPARQL Benchmark, and the DBpedia benchmark, a query workload that operates an
RDF representation of Wikipedia. Results reveal that the join algorithm used by
the system plays a critical role in dictating query runtimes. Distributed graph
databases must carefully optimize queries before generating MapReduce query
plans as network traffic for large datasets can become prohibitive if the query
is executed naively.
