The Cloud Database Benchmarking Experts
We believe in reliable, efficient and sustainable IT decision-making.
And we believe that there must be suitable software tools for these decision-making processes.
That is why we are developing a science-based benchmarking platform that helps to efficiently solve the IT challenges of our time.
benchANT's founders and benchmarking experts:
Dr. Jörg Domaschka (left) and Dr. Daniel Seybold (right)
Two Benchmarking Domains
Classic database benchmarking is difficult, but cloud database benchmarking is even more complicated as two previously independent IT domains need to be understood.
Our co-founders Daniel and Jörg combine their domain expertise and experience. The result is benchANT's unique service portfolio and Benchmarking-as-a-Service platform.
Dr. Daniel Seybold
-
Media informatics studies (M.Sc.) at the Ulm University, Germany
-
6 years of scientific research on cloud database benchmarking
-
more than 10 scientific publications in the field of cloud database benchmarking
-
Doctoral thesis: An Automation-based Approach for Reproducible Evaluations of Distributed DBMS on Elastic Infrastructures
Dr. Jörg Domaschka
-
Holds diploma (Dipl. Inf.) from University of Erlangen-Nuremberg and PhD from Ulm University.
-
14 years of scientific research in the field of distributed systems and performance engineering with more than 40 scientific publications
-
Doctoral thesis: A Comprehensive and Flexible Approach to Transparent Replication of Java Services and Applications
Benchmarking findings from research and development
FINDING 1
Connections are complex and measurements are sensitive
FINDING 2
simple measurment methods quickly lead to incorrect results
FINDING 3
experience and expertise are required for reliable results
The benchANT team in 2022
Company History
benchANT offers a benchmarking-as-a-service platform for cloud and database decision-making and optimisation. The company is a spin-off of the University of Ulm, Germany and is funded by the EXIST research transfer grant until the end of 2022.
benchANT is based on the long-standing research activities of the two founders, Dr. Daniel Seybold and Dr. Jörg Domaschka. The obvious need for quantitative decision-making is based on meaningful performance measurement data in the two IT domains of public cloud and database management systems led to the creation of the company.
The founding team was completed by Jan Ocker.
Since February 2022, benchANT is an independent company in the legal form of a limited liability company ("GmbH"). The founding team also represents the management.
Funding and Networks
Awards
benchANT is the winner of the "CyberOne Hightech Awards BW 2021" in the category "ICT, Media and Creative Industries".
The CyberOne is the central business plan competition of the high-tech industries in Baden-Württemberg, Germany.
It is sponsored by the Baden-Württemberg Ministry of Economics, Labour and Tourism and numerous industrial companies.
Funding
The benchANT project and the company was funded by the EXIST-Forschungstransfer programme.
The EXIST Forschungstransfer funding is financed by the Federal Ministry for Economic Affairs and Energy (BMWi) and the European Social Fund (ESF).
It supports ambitious technology-oriented start-ups from universities and non-university research institutions.
Startup Networks
Startup network: bwcon
Accelerator: M.Tech
Incubator: RWTH Aachen Incubator Programme - Fall Batch 2021
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.
2021 - Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads
by Jörg Domaschka, Mark Leznik, Daniel Seybold, Simon Eismann, Johannes Grohmann, Samuel Kounev >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
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 >Read
Framework for analyzing the high availability of distributed database systems
2017 - Is distributed database evaluation cloud-ready?
by Daniel Seybold, Jörg Domaschka >Read
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 >Read
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 >Read
Presentation of Cloudiator, a Corss cloud toolset for automated management of applications across multiple cloud providers.
2014 - Reliability and availability properties of distributed database systems
by Jörg Domaschka, Christopher B Hauser, Benjamin Erb >Read
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 >Read
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 >Read
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.
