This paper examines what types of databases that could be useful in clearing house systems, focusing on one of Nasdaq's clearing house systems. To determine this, the reports start by looking at what characteristics are important for the database used in a clearing house system. Based on this information, databases that fit these characteristics, like SQLite, MongoDB, Couchbase lite, and Nasdaq's own database, were used in tests to give an overview of their performances related to both latency and throughput. The test results are then analyzed to determine what database has the best performance under different conditions. This paper concluded that Nasdaq's current database is a good fit for this specific system and that the other databases would most likely not result in the same or similar performances. While the other databases, in general, performed worse compared to the current solution, H2 did have better results in some of the tests.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-227186 |
| Date | January 2024 |
| Creators | Hägglund, Casper |
| Publisher | Umeå universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UMNAD ; 1490 |
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