Claude Barthels

PhD Candidate, Systems Group, ETH Zurich

Photo of Claude taken in February 2017.

Since Autumn 2013, I am a PhD candidate in the ETH Systems Group, working under the supervision of Prof. Dr. Gustavo Alonso. My research focuses on database systems, in particular distributed query processing on modern hardware. Prior to joining the Systems Group, I received my Master of Science degree from ETH Zurich in September 2013, with my focus area being distributed systems. My master thesis on distributed join algorithms was supervised by Prof. Dr. Donald Kossmann and Dr. Simon Loesing.


Claude Barthels, Ingo Müller, Timo Schneider, Gustavo Alonso, Torsten Hoefler
Distributed Join Algorithms on Thousands of Cores. VLDB 2017, Munich, Germany. [PDF] [BibTeX]
Darko Makreshanski, Jana Giceva, Claude Barthels, Gustavo Alonso.
BatchDB: Efficient Isolated Execution of Hybrid OLTP + OLAP Workloads. SIGMOD 2017, Chicago, United States. [To appear]
Claude Barthels, Gustavo Alonso, Torsten Hoefler
Designing Databases for Future High-Performance Networks. IEEE Bulletin on Data Engineering 2017, Vol. 40, No. 1. [To appear]
Claude Barthels, Simon Loesing, Gustavo Alonso, Donald Kossmann
Rack-Scale In-Memory Join Processing using RDMA. SIGMOD 2015, Melbourne, Australia. [PDF] [BibTeX]


Join Processing with RDMA: Modern communication mechanisms, such as Remote Direct Memory Access (RDMA), have significantly lowered the costs of large data transfers. However, these performance advantages can only be leveraged through interleaving the computation with the network communication and through careful management of the RDMA buffers used for transmitting and receiving data. In this project, we investigate how join operators need to be designed in order to take full advantage of all the features provided by modern low-latency, high-throughput networks. Our results show that hardware-concious distributed join algorithms can run on thousands of cores and exhibit good performance and scalability. FDR InfiniBand Cluster at ETH Zurich
Rack-Scale Data Processing Systems: Rack-scale computers are becoming the building blocks of modern data centers. They are characterized by new hardware technologies that promise terabytes of main memory and thousands of processor cores connected through high-speed networks. These systems face a variety of challenges, one of which is the orchestration of the processing and communication resources in order to achieve maximum performance. In this project, we explore how to design databases for rack-scale systems. We investigate several approaches for distributing a state-of-the-art relational database on a modern rack-scale cluster and evaluate these techniques in terms of performance, fault-tolerance, scalability, and elasticity. QDR InfiniBand Cluster at ETH Zurich


ETH Systems Group, Zürich, Switzerland October 2013 – present
Research & Teaching Assistant
The Systems Group at ETH Zurich is a research and teaching collaboration among several professors in the general area of systems. My research focuses on distributed databases, in particular large-scale query processing. In addition to research, my duties include teaching activities at the under-graduate and graduate levels.
Oracle Labs, Redwood Shores, California, United States April 2014 – September 2014
Research Assistant
Internship as a research assistant at Oracle Labs, working on Project RAPID, a hardware-software co-design project targeting large-scale data management and analysis. Oracle Labs is the sole organization at Oracle which is devoted exclusively to research. Its mission is to identify and explore new technologies.
IBM Research, Rüschlikon, Switzerland October 2012 – January 2013
Research Assistant
Internship as a research assistant in the BlueZ Business Computing Group at the IBM Zurich Research Laboratory in Switzerland. IBM Research – Zurich is the European branch of IBM's worldwide research division and conducts fundamental and applied research that contributes to IBM products, services, and solutions.

Please contact me to receive my complete CV. References available upon request.