Query optimization on multi-model databases
As more businesses realized that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of systems that support the massive volume of non-relational or unstructured forms of data. The research focus of this job is to develop new principles and algorithms for a novel unified database management system to manage both well-structured data and NoSQL data.
- Learn how to use one or two multi-model databases.
- Perform the data loading and query processing with multi-model databases.
- Design an optimized way for data storage and query processing with multi-model databases.
The ideal candidate should be comfortable with using multi-model databases (e.g. ArangoDB).
1. Jiaheng Lu, Irena Holubová: Multi-model Databases: A New Journey to Handle the Variety of Data. ACM Comput. Surv. 52(3): 55:1-55:38 (2019) [PDF]
Category theory and functional programming on multi-model databases
We have developed a demo system, called MultiCategory, to process multi-model queries based on the category theory and functional programming. This project will further improve the system by adding some new features for MultiCategory, such as the update of the multi-model data and/or the connection with other databases.
- Learn basic knowledge of category theory.
- Learn how to use a functional programming language such as Haskell.
- Add new features for the MultiCategory system.
The ideal candidate should be comfortable with learning category theory and Haskell language.
See the Youtube Video on the MultiCategory system: