Dr. rer. nat. Jonas Traub
Senior Developer at SAP, working on Master Data Integration (MDI) as part of the Business Technology Platform (BTP). Former researcher at Technische Universität Berlin and the German Research Center for Artificial Intelligence (DFKI). Working with Volker Markl at DIMA and IAM.
I am Senior Developer at SAP, where I work on the Master Data Integration (MDI) Service, which is part of SAP's Business Technology Platform (BTP).
Formerly, I was a researcher at TU Berlin and DFKI working on stream processing systems, sensor data analysis, data acquisition, stream processing on modern hardware, and scalable data infrastructures.
I am a founding member and architect of the Nebula Stream Platform and the Agora Ecosystem.
In my PhD, I worked on damand-based data stream gathering, processing, and transmission.
I defended my PhD in March 2019 with Manfred Hauswirth as head of the committee and Volker Markl, Amr El Abbadi, and Albert Bifet as committee members.
I wrote my master thesis during a year abroad at the Royal Institute of Technology (KTH) and the Swedish Institute of Computer Science (SICS) / RISE in Stockholm under Supervision of Seif Haridi and Volker Markl and advised by Paris Carbone and Asterios Katsifodimos.
Prior to that, I received my B.Sc. degree at Baden-Württemberg Cooperative State University (DHBW Stuttgart) and worked several years at IBM in Germany and the USA.
I am alumnus of Software Campus, Studienstiftung des deutschen Volkes, and Deutschlandstipendium.
I am also head of the board of the alumni organization of Software Campus (SWCA e.V.).
Contact
firstname.lastname@tu-berlin.dePublications
- Book 2021
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Demand-based Data Stream Gathering, Processing, and Transmission: Efficient Solutions for Real-Time Data Analytics in the Internet of Things
Jonas Traub. BoD–Books on Demand, ISBN 9783752671254. - EDBT 2021
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Automatic Tuning of Read-Time Tolerances for Optimized On-Demand Data-Streaming from Sensor Nodes
Julius Hülsmann, Chiao-Yun Li, Jonas Traub, Volker Markl. 24th International Conference on Extending Database Technology (EDBT). [BibTeX] - TODS 2021
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Scotty: General and Efficient Open-source Window Aggregation for Stream Processing Systems
Jonas Traub, Philipp Grulich, Alejandro Rodríguez Cuéllar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl. ACM Transactions on Database Systems (TODS) 46 (1), 1-46. [BibTeX] - SIGMOD Record 2021
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Agora: Bringing together datasets, algorithms, models and more in a unified ecosystem [vision]
Jonas Traub, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Volker Markl. ACM SIGMOD Record 49 (4), 6-11. [BibTeX] - VLDB 2020
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Demand-based Sensor Data Gathering with Multi-Query Optimization
Julius Hülsmann, Jonas Traub, Volker Markl. Proceedings of the VLDB Endowment (PVLDB), 2020. [BibTeX] - DEBS 2020
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A Survey of Adaptive Sampling and Filtering Algorithms for the Internet of Things
Dimitrios Giouroukis, Alexander Dadiani, Jonas Traub, Steffen Zeuch, Volker Markl. ACM International Conference on Distributed and Event-Based Systems (DEBS), 2020. [BibTeX] - SIGMOD 2020
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Grizzly: Efficient Stream Processing Through Adaptive Query Compilation
Philipp M. Grulich, Breß Sebastian, Steffen Zeuch, Jonas Traub, Janis von Bleichert, Zongxiong Chen, Tilmann Rabl, Volker Markl. ACM SIGMOD International Conference on Management of Data, 2020. [BibTeX] - CIDR 2020
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The NebulaStream Platform: Data and Application Management for the Internet of Things
Steffen Zeuch, Ankit Chaudhary, Bonaventura Del Monte, Haralampos Gavriilidis, Dimitrios Giouroukis, Philipp M. Grulich, Sebastian Breß, Jonas Traub, Volker Markl. Conference on Innovative Data Systems Research (CIDR), 2020. [BibTeX] - PhD Thesis 2019
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Demand-based data stream gathering, processing, and transmission
Jonas Traub. Technische Universität Berlin, 2019. [BibTeX] - arXiv 2019
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SENSE: Scalable Data Acquisition from Distributed Sensors with Guaranteed Time Coherence
Jonas Traub, Julius Hülsmann, Sebastian Breß, Tilmann Rabl, Volker Markl. arXiv preprint arXiv:1912.04648, 2019. [BibTeX] - arXiv 2019
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Agora: Towards An Open Ecosystem for Democratizing Data Science & Artificial Intelligence
Jonas Traub, Zoi Kaoudi, Kaustubh Beedkar, Sergey Redyuk, Viktor Rosenfeld, Jorge-Arnulfo Quiané-Ruiz, Volker Markl. arXiv preprint arXiv:1909.03026, 2019. [BibTeX] - DEBS 2019
Git PDF Poster
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Generating Reproducible Out-of-Order Data Streams
Philipp M. Grulich, Jonas Traub, Asterios Katsifodimos, Sebastian Breß, Tilmann Rabl, Volker Markl. ACM International Conference on Distributed and Event-based Systems (DEBS), 2019. [BibTeX] - EDBT 2019
Best Paper Git
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Efficient Window Aggregation with General Stream Slicing
Jonas Traub, Philipp Grulich, Alejandro Rodríguez Cuéllar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX] - VLDB 2019
Git PDF Poster
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Analyzing Efficient Stream Processing on Modern Hardware
Steffen Zeuch, Bonaventura Del Monte, Jeyhun Karimov, Clemens Lutz, Manuel Renz, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl. Proceedings of the VLDB Endowment (PVLDB), 2019. [BibTeX] - EDBT 2019
Best Demo Git
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Resense: Transparent Record and Replay of Sensor Data in the Internet of Things
Dimitrios Giouroukis, Julius Hülsmann, Janis von Bleichert, Morgan Geldenhuys, Tim Stullich, Felipe Gutierrez, Jonas Traub, Kaustubh Beedkar, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX] - EDBT 2019
Git PDF Poster
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Adaptive Watermarks: A Concept Drift-based Approach for Predicting Event-Time Progress in Data Streams
Ahmed Awad, Jonas Traub, Sherif Sakr. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX] - ICDE 2018
Git Rec
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Scotty: Efficient Window Aggregation for out-of-order Stream Processing
Jonas Traub, Philipp M. Grulich, Alejandro Rodríguez Cuellar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl. IEEE International Conference on Data Engineering (ICDE), 2018. [BibTeX] - EDBT 2018
Git PDF Poster
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Scalable Detection of Concept Drifts on Data Streams with Parallel Adaptive Windowing
Philipp Marian Grulich, René Saitenmacher, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2018. [BibTeX] - EDBT 2018
Git PDF Poster
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Efficient SIMD Vectorization for Hashing in OpenCL
Tobias Behrens, Viktor Rosenfeld, Jonas Traub, Sebastian Breß, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2018. [BibTeX] - SoCC 2017
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Optimized On-Demand Data Streaming from Sensor Nodes
Jonas Traub, Sebastian Breß, Tilmann Rabl, Asterios Katsifodimos, and Volker Markl. In ACM Symposium on Cloud Computing 2017 (SoCC '17), Sep 25 - 27, 2017, Santa Clara, CA, USA. [BibTeX] - EDBT 2017
Best Demo Git Rec
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I²: Interactive Real-Time Visualization for Streaming Data
Jonas Traub, Nikolaas Steenbergen, Philipp M Grulich, Tilmann Rabl, and Volker Markl. Proceedings of the 20th International Conference on Extending Database Technology (EDBT'17), March 21-24, 2017, Venice, Italy. [BibTeX] - CIKM 2016
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Cutty: Aggregate Sharing for User-Defined Windows
Paris Carbone, Jonas Traub, Asterios Katsifodimos, Seif Haridi, and Volker Markl. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM'16), October 24 - 28, 2016, Indianapolis, Indiana, USA. [BibTeX] - it-Inf.T. 2016
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Apache Flink in current research
Tilmann Rabl, Jonas Traub, Asterios Katsifodimos, and Volker Markl. it-Information Technology, 58(4), 157-165, De Gruyter Oldenbourg, 2016. [BibTeX] - LWA 2015
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Die Apache Flink Plattform zur parallelen Analyse von Datenströmen und Stapeldaten
Jonas Traub, Tilmann Rabl, Fabian Hueske, Till Rohrmann, Volker Markl. Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. October 7 - 9, 2015, Trier, Germany. [BibTeX] - US Patent
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Adaptive Fragment Assignment for Processing File Data in a Database
Andrey Balmin, Romulo Antonio Pereira Goncalves, Fatma Ozcan, and Jonas Traub. US Patent 9,576,000 Β2, 2014. [BibTeX]
Talks and Panels
- code.talks 2019
Git PDF
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Talk - Scotty: Efficient Window Aggregation for your Stream Processing System
Jonas Traub, Philipp Grulich.
Code.Talks, Hamburg, Germany 2019. [BibTeX] - code.talks 2019
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Panel - GDPR-Who Cares? Is GDPR just a toothless tiger?
Panel about experiences with GDPR and the implications GDPR will have on Europe. Heike Wolters, Jonas Traub, Verena Grentzenberg & Wolfram Wingerath. Code.Talks, Hamburg, Germany 2019. - FlinkForward 2019
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Talk - Scotty: Efficient Window Aggregation with General Stream Slicing
Jonas Traub, Philipp Marian Grulich.
FlinkForward, Berlin, 2019. [BibTeX] - USA Excursion 2019
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Series of Talks: Database Research at TU-Berlin and DFKI IAM
Jonas Traub, Sebastian Breß, Andreas Kunft, Martin Kiefer, Juan Soto, Volker Markl. Hosts include: New York University (Center for Data Science), Harvard University (Data Systems Lab), Johns Hopkins University (Institute for Data Intensive Engineering and Science), Northeastern University (Data Lab), MIT (Database Group), University of Washington (Database Group), UC Berkeley (Database Group), Stanford University (Infolab), Confluent, IBM Almaden Research Center, Intel, Microsoft, Oracle, Snowflake, Workday. - FlinkForward 2018
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Talk - Efficient Window Aggregation with Stream Slicing
Jonas Traub, Philipp Marian Grulich.
FlinkForward, Berlin, 2018. [BibTeX] - BIRTE@VLDB 2018
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Panel - Are we making any attempts towards solving the hardest problems in stream processing today?
Panelists: Manpreet Singh (Google), Karthik Ramasamy (Stremlio), C. Mohan (IBM), Badrish Chandramouli (Microsoft), Neng Lu (Twitter), Alok Pareek (Striim), Jonas Traub (TU-Berlin). BIRTE Workshop at the 44th International Conference on Very Large Data Bases (VLDB), Brasil, Rio de Janeiro, September 2018. - Stream Reasoning 2018
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Talk - Optimized On-Demand Data Streaming from Sensor Nodes
Jonas Traub. Stream Reasoning Workshop 2018 at University of Zurich (UZH), Switzerland, January 2018. [BibTeX] - BDAHM/SDIC 2017
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Talk - Efficiently Handling Streams from Millions of Sesors
Jonas Traub. 2nd BMBF Big Data All Hands Meeting (BDAHM) and 2nd Smart Data Innovation Conference (SDIC), 11-12 October 2017, Karlsruher Institut of Technologie (KIT). - BDAHM/SDIC 2017
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Talk - Research and Innovation in the Berlin Big Data Center
Jonas Traub and Chen Xu with materials from Tilmann Rabl and Volker Markl. 2nd BMBF Big Data All Hands Meeting (BDAHM) and 2nd Smart Data Innovation Conference (SDIC), 11-12 October 2017, Karlsruher Institut of Technologie (KIT). - FlinkForward 2017
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Talk - I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink and Apache Zeppelin
Jonas Traub, Philipp Marian Grulich. FlinkForward, Berlin, 2017. [BibTeX] - BOSS@VLDB 2016
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Tutorial - Apache Flink Tutorial at the Big Data Open Source Systems Workshow
Konstantinos Kloudas (dataArtisans), Vasia Kalavri (KTH Stockholm), Jonas Traub(TU Berlin). Big Data Open Source Systems Workshow (BOSS) at VLDB, New Delhi, India, 2016. - DB2 User Grp. 2015
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Talk - Apache Flink - Stream and Batch Data Processing at Scale
Jonas Traub. DB2 User Group Meeting 2015, IBM Böblingen Research Lab.
Service
- VLDB 2021 - 47th International Conference on Very Large Data Bases - PC Member/Reviewer Research Track
- IEEE ICDE 2021 - 37th IEEE International Conference on Data Engineering - PC Member/Reviewer Research Track
- BTW 2021 - 19. GI Fachtagung für "Datenbanksysteme für Business, Technologie und Web" - PC Member/Reviewer Research Track
- ACM SIGMOD 2020 - International Conference on Management of Data - PC Member/Reviewer Demonstration Track
- Springer Journal: Data Mining and Knowledge Discovery - Reviewer
- IEEE Transactions on Industrial Electronics - Reviewer
- WBDB 2015 - 6th International Workshop on Big Data Benchmarking - PC Member/Reviewer
- Studienstiftung des Deutschen Volkes - Voluntary member of the admission board
Theses & Teaching
Thesis Supervision
- Juliane Verwiebe: A Catalog of Window Types for Stream Processing Systems
- Andrej Savinov: Enabling Unified Efficient Window Aggregation on Open Source Stream Processing Engines
- Batuhan Tüter: Evaluating Window Aggregation Techniques on Stream Processing Engines
- Alexander Dadiani: A Catalogue of Sampling Algorithms for Sensor Data
- Chiao-Yun Li: Automatic Tuning of Read-Time Tolerances for on-demand Data Streaming
- Vianney de Cibeins: A Benchmark for Adaptive Data Collection in the Internet of Things
- Yusuf Güven Toprakkiran: Machine learning from streaming data in heterogeneous computing environments
- Alejandro Rodriguez Cuellar: Window aggregate sharing for out-of-order stream processing
- Jerred Blankenburg: Performance Analysis of a Complex Event Processing Engine on classical data-stream-processing workloads
- Robin Rabe: Scalable Data Stream Processing Using Cloud-Based Database Management Systems
Teaching
Winter Term 2020/2021
Winter Term 2018/2019
- IDBPRA: Database Internals & Scalable Data Processing
- Streaming Systems Lecture for Advanced Information Management 3
Summer Term 2018
- BDAPRO: Big Data Analytics Project - Project Mentor
- Streaming Systems Lecture for Advanced Information Management 3
Winter Term 2017/2018
- IDBPRA: Database Internals & Scalable Data Processing
- BDAPRO: Big Data Analytics Project - Project Mentor
- Streaming Systems Lecture for Advanced Information Management 3
Summer Term 2017
- BDAPRO: Big Data Analytics Project
- Streaming Systems Lecture for Advanced Information Management 3
Winter Term 2016/2017
- IDBPRA: Database Internals & Scalable Data Processing
- Streaming Systems Lecture for Advanced Information Management 3
Summer Term 2016
- BDAPRO: Big Data Analytics Project
- Streaming Systems Lecture for Advanced Information Management 3
Winter Term 2015/2016
- DBT: Scalable Data Processing
- IDBPRA: Database Internals & Scalable Data Processing
- Streaming Systems Lecture for Advanced Information Management 3
Summer Term 2015
- Streaming Systems Lecture for Advanced Information Management 3
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