The Cloud Database Benchmarking Experts
Classic database benchmarking is difficult, but cloud database benchmarking is even more complicated.
Two previously independent IT domains - databases and cloud - need to be understood and measured together.
The two co-founders Dr. Daniel Seybold and Dr. Jörg Domaschka combine their domain expertise and experience. The result is benchANT's unique Benchmarking-as-a-Service platform.
Find out what distinguishes this expertise and learn more about the long, insightful journey the two experts have taken together.
2
independent IT domains.
benchmarking experts.
20 years
performance engineering experience.
The Two Experts and Co-founders of benchANT
Dr. Daniel Seybold
- Media informatics studies (M.Sc.) at the University of Ulm
- followed by 6 years of scientific research on cloud database benchmarking
- more than 10 scientific publications in the field of cloud database benchmarking
- Doctoral thesis (Magna cum Laude): An Automation-based Approach for Reproducible Evaluations of Distributed DBMS on Elastic Infrastructures
Dr. Jörg Domaschka
- Studied computer science (Dipl. Inf.) at the University of Erlangen-Nuremberg
- followed by 14 years of scientific research in the field of distributed systems and performance engineering
- more than 40 scientific publications in the field of distributed systems and performance engineering
- PhD thesis (Summa cum Laude): A Comprehensive and Flexible Approach to Transparent Replication of Java Services and Applications
Research & Publications on Clouds and Databases
Since 2011, benchANT's two technical founders have contributed to more than 120 scientific publications in the area of cloud computing, distributed systems, databases, and their performance, scalability, availability, and elasticity.
We highlight some core publications in more detail here, as they deepen the understanding and benefits of cloud & database benchmarking and clearly illustrate benchANT's approach.
The complete publication list of the two founders can be found on Google Scholar:
Publications Dr. Jörg Domaschka
Publications Dr. Daniel Seybold
2021 - Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads: Vision Paper
by Jörg Domaschka, Mark Leznik, Daniel Seybold, Simon Eismann, Johannes Grohmann, Samuel Kounev | Link
Designing synthetic benchmarks based on real workload traces for "what-if" benchmarking scenarios. Simulation of hypothetical scaling workloads as well as anomalies in benchmarking measurements.
2020 - Hathi: An MCDM-based Approach to Capacity Planning for Cloud-hosted DBMSs
by Jörg Domaschka, Simon Volpert, Daniel Seybold | Link
An evaluation-based Multi Criteria Decision-Making (MCDM) framework for planning cloud-hosted distributed DBMSs with respect to throughput, latency, cost, consistency, availability, and stability.
2020 - Baloo: Measuring and modeling the performance configurations of distributed DBMSs
by Johannes Grohmann, Daniel Seybold, Simon Eismann, Mark Leznik, Jörg Domaschka | Link
Framework for systematic measurement and modeling of various performance-relevant configurations of distributed DBMSs in cloud environments. Dynamic estimation of the required number of measurement configurations as well as the number of required measurement repetitions per configuration based on a desired target accuracy.
2020 - Towards Understanding the Performance of Distributed Database Management Systems in Volatile Environments
by Jörg Domaschka, Daniel Seybold | Link
Experiences with performance evaluation of DBMSs hosted in the cloud to find well-suited configurations for specific use cases. Workload dependencies, cloud environment and DBMS with different parameters.
2020 - King Louie: reproducible availability benchmarking of cloud-hosted DBMSs
by Daniel Seybold, Stefan Wesner, Jörg Domaschka | Link
Evaluation of availability and performance guarantees of distributed DBMSs with high availability mechanisms in case of cloud resource failures. Benchmarking process with fault injection and 16 availability evaluations.
2020 - Performance Results of a Containerized MongoDB DBMS
by Daniel Seybold, Christopher B Hauser, Georg Eisenhart, Simon Volpert, Jörg Domaschka | Link
Dataset with performance KPIs on different containerized MongoDB setups, focusing on the impact of storage hardware.
2019 - Kaa: Evaluating elasticity of cloud-hosted dbms
by Daniel Seybold, Simon Volpert, Stefan Wesner, André Bauer, Nikolas Herbst, Jörg Domaschka | Link
Automated evaluation process for the elasticity of distributed DBMSs. Case study with significant elasticity scenarios.
2019 - The cloud application modeling and execution language
by Achilleas P Achilleos, Kyriakos Kritikos, Alessandro Rossini, Georgia M Kapitsaki, Joerg Domaschka, Michal Orzechowski, Daniel Seybold, Frank Griesinger, Nikolay Nikolov, Daniel Romero, George A Papadopoulos | Link
Defining the Cloud Application Modeling and Execution Language (CAMEL) as a multi-cloud modeling language.
2019 - A survey on data storage and placement methodologies for cloud-big data ecosystem
by Somnath Mazumdar, Daniel Seybold, Kyriakos Kritikos, Yiannis Verginadis | Link
Management of Big Data and data storage in the cloud with a focus on non-functional aspects such as performance. Technology comparison and gap analysis.
2019 - SORRIR: A Resilient Self-organizing Middleware for IoT Applications
by Jörg Domaschka, Christian Berger, Hans P Reiser, Franz J Hauck, Gerhard Habiger, Frank Griesinger, Matthias Tichy, Jakob Pietron, Philipp Eichhammer | Link
Position paper of a robust and self-organizing execution platform for IoT applications.
2019 - Mowgli: Finding your way in the dbms jungle
by Daniel Seybold, Moritz Keppler, Daniel Gründler, Jörg Domaschka | Link
Database evaluation framework for data-intensive technologies like Big Data and IoT with cloud resources.
2018 - The impact of the storage tier: A baseline performance analysis of containerized dbms.
by Daniel Seybold, Christopher B Hauser, Georg Eisenhart, Simon Volpert, Jörg Domaschka | Link
Evaluation method for the performance overhead of containerized DBMSs by combining three operating models and two storage backends
2018 - A Provider-Agnostic Approach to Multi-cloud Orchestration Using a Constraint Language.
by Daniel Baur, Daniel Seybold, Frank Griesinger, Hynek Masata, Jörg Domaschka | Link
Multi-cloud constraint language for application and resource description for requirements analysis and bid matching with the goal of independent vendor selection.
2017 - Gibbon: An availability evaluation framework for distributed databases.
By Daniel Seybold, Christopher B Hauser, Simon Volpert, Jörg Domaschka | Link
Framework for analyzing the high availability of distributed database systems
2017 - Is distributed database evaluation cloud-ready?
by Daniel Seybold, Jörg Domaschka | Link
Cloud-centric analysis of distributed database evaluation frameworks based on performance, scalability, elasticity and consistency.
2016 - Is elasticity of scalable databases a myth?
by Daniel Seybold, Nicolas Wagner, Benjamin Erb, Jörg Domaschka | Link
Scalability and elasticity studies of Couchbase, Cassandra and MongoDB.
2015 - Cloudiator: a cross-cloud, multi-tenant deployment and runtime engine
by Jörg Domaschka, Daniel Baur, Daniel Seybold, Frank Griesinger | Link
Presentation of Cloudiator, a Corss cloud toolset for automated management of applications across multiple cloud providers.
2014 - The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation
by Per-Olov Östberg, Henning Groenda, Stefan Wesner, James Byrne, Dimitrios S Nikolopoulos, Craig Sheridan, Jakub Krzywda, Ahmed Ali-Eldin, Johan Tordsson, Erik Elmroth, Christian Stier, Klaus Krogmann, Jörg Domaschka, Christopher B Hauser, Peter J Byrne, Sergej Svorobej, Barry Mccollum, Zafeirios Papazachos, Darren Whigham, Stephan Rüth, Dragana Paurevic | Link
Automation and optimization of cloud infrastructures with the 3 goals of 1) modeling applications and data center resources, 2) simulating applications and resources for planning and operations, and 3) autonomous optimization of application deployment and resource utilization.
2014 - Towards a generic language for scalability rules
by Jörg Domaschka, Kyriakos Kritikos, Alessandro Rossini | Link
Scalability Rules Language (SRL) for the specification of scalability rules in multi-cloud applications.
2014 - Reliability and availability properties of distributed database systems
by Jörg Domaschka, Christopher B Hauser, Benjamin Erb | Link
Classification of non-functional database properties such as replication, consistency, conflict management and partitioning.
2013 - Beyond IaaS and PaaS: An extended cloud taxonomy for computation, storage and networking
by Steffen Kächele, Christian Spann, Franz J Hauck, Jörg Domaschka | Link
Tiered taxonomy for computation, storage and networking services of cloud computing based on performance aspects
2011 - COSCA: an easy-to-use component-based PaaS cloud system for common applications
by Steffen Kächele, Jörg Domaschka, Franz J Hauck | Link
Comparison of cloud computing in theory with currently existing PaaS solutions for typical business applications. Identification of 11 requirements and comparison with the state of the art. Development of an ideal-typical PaaS system.
over 120 scientific research papers
more than 20 years of cloud and database research