Master Thesis Intern - Time series support

Time series data plays a critical role in various domains, including finance, healthcare, IoT, and more. Managing, storing, and analyzing time series data efficiently is a significant challenge. This master's student project aims to extend MonetDB, a powerful open-source analytical database system, with specific support for time series data. The project will focus on enhancing MonetDB's capabilities to efficiently store, query, and analyze time series data.

Project Goals

  • Time Series Data Model: Develop a data model within MonetDB to represent time series data efficiently. This model should handle irregular time series data, which is common in real-world applications.
  • Data Ingestion: Implement methods for ingesting time series data into MonetDB from various sources, including CSV files, data streams, and IoT devices. Ensure support for different time series formats and data quality checks during ingestion.
  • Indexing and Compression: Create indexing mechanisms tailored for time series data to speed up query performance. Implement compression techniques to minimize storage requirements while maintaining data integrity.
  • Time Series Query Language: Extend the MonetDB query language to include time series-specific operators and functions. Support common time series operations like windowing, aggregation, and interpolation.
  • Visualization and Analytics Integration: Integrate libraries or tools for time series visualization and advanced analytics (e.g., forecasting, anomaly detection) with MonetDB. This may involve developing connectors or APIs.
  • Performance Benchmarking: Conduct comprehensive performance benchmarks to evaluate the efficiency of MonetDB with time series data. Compare its performance to existing time series databases to highlight strengths and areas for improvement.
  • Documentation and User Guides: Create user-friendly documentation and guides for using the extended MonetDB with time series data. This will help potential users understand how to leverage the new capabilities.
  • Testing and Validation: Rigorously test the extended MonetDB with real-world time series datasets and use cases. Verify that it can handle large-scale time series data and provide accurate results.

Expected Outcomes

  • A modified version of MonetDB with enhanced support for time series data.
  • Efficient storage and retrieval of time series data within MonetDB.
  • Improved query performance on time series data.
  • Integration with time series analysis and visualization tools.
  • Benchmark results highlighting the advantages of the extended MonetDB.
  • Comprehensive documentation and user guides.

Skills and Requirements:

This project requires knowledge of database management systems, SQL, data modeling, indexing, and programming in languages like C and SQL. Additionally, experience with time series data processing, compression techniques, and benchmarking tools would be beneficial.


The project is expected to be completed within the duration of a typical master's program, which is typically 1-2 academic semesters.

Potential Extensions

Depending on the project's progress and available resources, potential extensions could include:

  • Implementing advanced machine learning algorithms for time series analysis within MonetDB.
  • Enhancing security features for time series data stored in MonetDB.
  • Developing a user-friendly graphical interface for managing time series data in MonetDB.


This project will advance MonetDB as a database system optimized for analytical and machine learning workloads, making it a valuable asset for researchers and organizations working in these fields. It will enhance your knowledge and expertise in database systems, efficient time series data management and analysis, and system-level programming, providing a strong foundation for further academic and professional pursuits.


This position is mainly targeted towards students of Dutch educational institutions. Unfortunately, we cannot support international students. Before starting the project, consult with your academic advisor or thesis committee to align the project with your program's requirements and expectations. Collaborate with MonetDB developers to receive guidance and support throughout the process, especially considering the specialized nature of this project. The position requires physical presence for at least three days per week for the duration of the project.

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