Below image shows the database structure as a relational database schema. These represent many-to-many relationships between entities. Relationships between the entities are stored in relationship tables of worktarget, workinvoice, useditem and workhours. These tables contain the customer information, customer’s invoices, the target (or project) where the work is performed, a listing of each work, and a listing of different worktypes with different prices and information about the items used for each work. The basic tables customer, invoice, target, work, worktype and item represent entities of the application domain. Graph databases outperformed relational databases with workloads that mainly consisted of multiple table joins, pattern matching, path identification and their combinations. The conclusion of the tests was that relational databases outperformed graph databases with workloads that mainly consisted of group by, sort, aggregation operations and their combinations. Different types of query workloads were tested, including atomic relational queries such as projection, aggregation, join and order by, TPC-H workloads, and different graph query algorithms. Four relational datasets from TPC-H benchmark were used as well as four real graph datasets. compared RocksDB 5.8, Hbase 2.2, Cassandra 3.11, Neo4j 3.4.6 and MySQL 5.7. One of the goals of this study was to identify differences in what use case the databases should be used.Ĭheng et al. As all of the databases researchers studied are quite popular and are often candidates for use in enterprises. Sixth is the relevance in social networks which is counted by the number of tweets on Twitter, in which the system is mentioned. Fifth is the number of profiles in LinkedIn in which the system is mentioned. Fourth is the number of job offers in Indeed and Simply Hired. Third is the frequency of technical questions in Stack Overflow or DBA Stack Exchange. Second is the general interest which is measured by frequency in Google Trends. The first parameter is the number of mentions on the websites Google and Bing. Popularity is measured using six parameters. DB-Engines ranks the databases according to current popularity. Neo4j ranks 1st out of 32 graph databases on the same sites. Based on the popularity of databases, the DB-Engines site ranks MariaDB as 8th out of 138 of relational databases. From this perspective, MariaDB is a natural choice for a modern database, because MariaDB was initially a descendant of MySQL. Researchers considered all these optimizations in the efficiency evaluations.Īn older MySQL version was included in the comparison to make the research compatible with earlier studies.
Recursive queries can be optimized in modern versions of Neo4J. Additionally, for the selected graph database system (Neo4J), a more efficient query execution type (call-function) was developed. Indexing is a traditional method to improve performance and it can be applied with both relational and graph databases.
In addition to using complex queries, researchers also paid attention to factors related to efficiency. Thus, they belong to the same database system family, and their comparison is an indication of how relational database query efficiency has developed during the last decade. MariaDB and MySQL 8 were initially based on MySQL 5.1. Old MySQL 5.1 was included to observe the efficiency development of relational database systems. MySQL 8 was included in the present investigation in order to compare how the query performance of complex queries differs between MySQL and MariaDB. MariaDB was selected because it is a modern database system and, to the best of the knowledge, it has not been compared to graph database systems before. MariaDB and two versions of MySQL were selected as relational database systems.
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