Thesis: Performance evaluation of time-series and traditional databases for high frequency workloads
Knightec Group ABOm tjänsten
High Level Description
The increase in IoT devices has led to a rapid growth in time-series data. While traditional relational databases are commonly
used to store such data, specialized time-series databases have emerged claiming improved performance, scalability, and storage
efficiency for time-stamped workloads.
Investigate ideal conditions for large time sorted data.
Project Description
This thesis aims to compare modern time-series databases with traditional relational database solutions and evaluate their
suitability for different workloads. The study will focus on key performance metrics such as data ingestion rate, query response
time, storage efficiency, and resource utilization under large data volumes and access patterns.
Who are we looking for?
- Fluency in English, both written and spoken
Purpose
- What table structures and indexing patterns optimize large time-series data sets both within traditional and time-series
databases?
An Exciting Journey with Knightec Group
Semcon and Knightec have joined forces as Knightec Group. Together, we are Northern Europe’s leading strategic partner in
product and digital service development. With a unique combination of cross-functional expertise and a holistic business
understanding, we help our clients realize their strategies – from idea to complete solution.
Practical Information
This is a thesis position, located at our office in Sundsvall. Start date January or March 2027.
Please submit your application as soon as possible, but no later than 2026-11-30. If you have any questions, you are welcome to
contact johanna.edstrom@knightec.se. Note that due to GDPR, we only accept applications through our careers page.