Real Time Data Management

Data management for real time challenges

Real time reactivity is increasingly becoming a crucial success factor for industry and commerce. Only if changes relevant for business are detected immediately, enterprises can react appropriately to emerging conflicts or new business opportunities. Our application areas for real time processing of large amounts of data are for instance:

  • Logistics: Transport companies can optimise their networks in real time.
  • IT Services: Complex IT infrastructures can be managed in real time according to the current load and available resources.
  • Social media: Companies can react in real time to relevant social media dialogues on Twitter etc. and intervene, for example before the situation escalates.
  • Health care system: Health insurance companies and other health associations can offer their members applications. In addition to the evaluation of data of wearable body sensors, these applications provide external knowledge that is processed in real time by the recording of data of other users. Thus, the health associations and health insurance companies can promote healthy sporting activities.

Of course, we take into consideration the requirements of data protection and security within all of our projects and applications.

Our strengths

At the FZI, we realise real time reactivity through complex event processing (CEP) on data streams with high throughput. Thus, our strength is to consider the life cycle of such systems from a holistic perspective – starting with intuitive, user-friendly modelling of situations that must be recognised in real time due to their criticality, to the automated refinement of event rules and through to the detection of complex situations and events that could not be processed in real time yet. The aim of the integration of semantic technologies into real time processing is to recognise the exact situation that is of interest in the respective context.

Our experience

In the field of real time capability, we can fall back on varied experiences gained in national and international research projects as well as in industry-related projects with small and medium-sized enterprises and concerns.

It does not make a difference whether the relevant data streams are generated by sensors, the web or business applications. For instance, in the EU project ALERT data was integrated from various collaboration systems such as wikis, message boards and source code managements in order to minimise the coordination effort in software development projects. In the project PLAY a marketplace was created out of the Internet of Things and social media sources in order to link data sources in real time. In another project of the FZI in cooperation with EnBW, a German energy supply company, the focus lied on the application of complex event processing in the context of smart grids.


Our services

We are your partner in research and support you with great knowhow in modern real time data processing. We are looking forward to your project ideas, for instance on the following topics:

  • Big data and fast data
  • Real time processing
  • Mobile sensing

We investigate markets, technologies and methods on your behalf, we develop prototypical solutions for you or advise you individually and independently of manufacturers and providers in opportunities for a product, workflows, processes, and structures. Please feel free to contact us. We are looking forward to your request.

Contact person

Dr.-Ing. Dominik Riemer




Dominik Riemer studierte Informationswirtschaft am Karlsruher Institut für Technologie (KIT). Von 2011 bis 2016 arbeitete er als Wissenschaftlicher Mitarbeiter und später als Projektleiter am FZI bei Prof. Dr. Studer im Forschungsbereich IPE mit dem Schwerpunkt Complex Event Processing (CEP). Anschließend war er von Januar 2017 bis März 2019 Abteilungsleiter "Wissensmanagement" am FZI. Seit Oktober 2018 verantwortet er gemeinsam mit Dr.-Ing. Fabian Rigoll den Forschungsbereich "Information Process Engineering".

Dominik Riemer ist Experte für technische Fragestellungen bzgl. ereignisgesteuerter Architekturen, verteilter Systeme und Datenstromverarbeitung. Im Rahmen seiner Tätigkeit arbeitet er als Projektmitarbeiter, Projektleiter und wissenschaftlicher Koordinator in zahlreichen öffentlichen Forschungsprojekten (z.B. ProaSense (EU), ALERT (EU), PostBot-E (BMWi), PartSense (BMBF), WEKOVI (BMVI)) und berät Großunternehmen wie Bosch und BASF sowie KMU bei der Umsetzung innovativer Lösungen für Echtzeitverarbeitung und IoT in Domänen wie Mobilität, Produktion und Logistik.

2016 promovierte Dominik Riemer am Karlsruher Institut für Technologie (KIT) summa cum laude zum Thema "Methods and Tools for Management of Distributed Event Processing Applications". Die Arbeit wurde ausgezeichnet mit dem Wissenschaftspreis der KIT-Fakultät für Wirtschaftswissenschaften.

Seine derzeitigen Forschungsinteressen liegen im Bereich des intelligenten Datenmanagements für Stream Processing und Fog Computing, dabei insb. der Zugänglichmachung komplexer echtzeitfähiger und hochskalierbarer Analytics-Verfahren und -Anwendungen für Fachanwender.



  • Stream Processing 
  • Fog Computing
  • Self-Service Big Data Analytics / Guided Analytics
  • Distributed Systems


  • Apache StreamPipes: A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams (
  • Lieferbot-E (BMWi Elektromobilität): Automatisierte Ver- und Entsorgung städtischer Quartiere durch autonome Elektrofahrzeuge
  • OCROSS (BMVI mFUND): Open Data Crowd Sensing Service für die einfache Fusion annotierter und schwarmbasierter Massendaten
  • WEKOVI (BMVI mFUND): Werkzeuge für die einfache Erstellung komplexer Vergleichsindizes
  • ProveIT (BMWi Zukunftsfähige Logistiknetzwerke): Echtzeitbasierte Störungserkennung und -behebung in Logistikprozessen 
  • ProaSense (EU FP7): The Proactive Sensing Enterprise, Datengetriebene proaktive Erkennung von Störungen in Produktionsprozessen
  • ALERT (EU FP7): Echtzeitkoordination und Kollaboration von Entwicklern in Softwareprojekten 
  • ReFLEX (EU FP7 SME): Ad-hoc Prozessadaptionen im Logistikumfeld
  • PartSense (DE KMU-Innovativ): Anwendungen und Technologien für Participatory Sensing 


zu den Publikationen


Telefon: +49 721 9654-724