2023, Espona, Lucía, Vichalkovski, Anton, Steingartner, William, Pustulka, Elzbieta, Abelló, Alberto, Vassiliadis, Panos, Romero, Oscar, Wrembel, Robert, Bugiotti, Francesca, Gamper, Johann, Vargas Solar, Genoveva, Zumpano, Ester

We present a new method for automated index suggestion for MongoDB, based solely on the queries (called aggregation pipelines), without requiring data or usage information. The solution handles complex aggregations and is suitable for both cloud and standalone databases. We validated the algorithm on TPC-H and showed that all suggested indexes were used. We report on the performance and provide hints for further development of an automated method of index selection. Our algorithm is, to the best of our knowledge, the first query-based solution for automated indexing in MongoDB.

2022, Espona, Lucía, Pustulka, Elzbieta, Chiusano, Silvia, Cerquitelli, Tania, Wrembel, Robert, Nørvåg, Kjetil, Catania, Barbara, Vargas-Solar, Genoveva, Zumpano, Ester

Data versioning is required in various business and science contexts, including governance, risk and compliance (GRC) and is essential for security audits, legal compliance and business strategy development. We present a data versioning library for MongoDB to support an innovative enterprise resource planning (ERP) system for small and medium enterprises (SMEs) which aims to be flexible and adapt to changing business needs. We exploit the fact that the volume of archival data is orders of magnitude larger than of the currently valid documents and that historic data is rarely accessed. Experiments with eight sets of 1 million mutations/queries on 100K of valid documents (average size 2.3 kB), carried out over a period of 60 h on a local PC show stable average versioning write/read operation performance per document in the range of 12.3/1.2 ms which proves that the solution is viable in an SME scenario.

2022, Pustulka, Elzbieta, von Arx, Stefan, Espona, Lucía

Enterprise Resource Planning (ERP) systems are needed in many business activities. SMEs (small and medium enterprises) are not well served by current ERPs, as such systems are hard to tailor. This prompts us to experiment with building an ERP on top of a NoSQL database, which intends to be more flexible, as it is based on JSON and not on a relational data model. We present a novel ERP solution specifically designed to grow and evolve as the world changes. The ERP is for a service company which bills for time spent on customer projects. The work involves various challenges: data modelling, query specification, write and read performance analysis, versioning, user interface generation, and query optimisation. Here, we report on the performance of a NoSQL ERP using MongoDB and show that writes are fast and queries and reports are fast enough.