Renata Borovica-Gajic

I obtained my PhD from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. During my PhD studies, I worked in the Data-Intensive Applications and Systems Laboratory (DIAS) supervised by Prof. Anastasia Ailamaki. My research focuses on enabling faster, more predictable and cheaper data analysis. To optimize performance and cost of data analytics services, I envision database systems as adaptive engines able to adjust their query execution strategy at runtime to fit the characteristics of the queries, data and underlying hardware. I am also interested in the broad topic of scientific data management, data exploration, query optimization, physical database design, and hardware-software co-design. More details can be found in my CV.

Renata Borovica-Gajic photo


Cheap data analysis with Skipper

This project looks at exploiting new hardware to decrease the cost of data analytics storage infrastructure. In particular, Skipper is an end-to-end query processing framework built by using cold storage devices as an underlying storage medium. Skipper employs a (cold) storage-driven query execution model based on multi-way joins combined with efficient cache management and I/O scheduling strategies to hide the non-uniform access latencies of cold storage. As a result, Skipper offers performance comparable to the performance of systems storing data on HDD, with a substantially lower cost. PDF

Predictable query performance with Smooth Scan

Smooth Scan aims at preventing performance degradation coming from suboptimal query plan decisions. To achieve optimal performance for all query inputs, Smooth Scan uses continuous adaptation and morphing at runtime by transforming from one physical alternative to another (i.e., from an index access to sequential scan). With Smooth Scan, an access path strategy is progressively transformed into an optimal form based on the operator selectivity and result distribution observed during query execution. As a result, a system with Smooth Scan requires no access path decisions up front nor does it need accurate statistics to provide good performance. PDF

Fast data exploration with NoDB

NoDB enables fast and efficient data exploration by removing data loading as a prerequisite to data querying. Instead, NoDB enables query processing capabilities directly over data files, and uses the user queries as a driver for partial and incremental data loading and performance tuning. To mask the overhead of raw file data access and speed up future queries, NoDB builds and progressively refines auxiliary design structures (positional indexes, data caches and statistics) during query execution. As a result, NoDB matches the performance of traditional database systems that process already loaded data. PDF


PhD Thesis, EPFL, 2016. Toward timely, predictable and cost-effective data analytics. R. Borovica-Gajic. PDF Slides Poster

VLDB, 2016. Cheap Data Analytics Using Cold Storage Devices. R. Borovica-Gajic, R. Appuswamy, and A. Ailamaki. PDF Slides Poster

ICDE, 2015. Smooth Scan: Statistics-oblivious Access Paths. R. Borovica-Gajic, S. Idreos, A. Ailamaki, M. Zukowski and C. Fraser. PDF Slides Poster

ACM, Research Highlights, 2015. NoDB: Efficient Query Execution on Raw Data Files. I. Alagiannis, R. Borovica-Gajic, M. Branco, S. Idreos, and A. Ailamaki. PDF

VLDB, 2012. NoDB in Action: Adaptive Query Processing on Raw Data (demo). I. Alagiannis, R. Borovica, M. Branco, S. Idreos and A. Ailamaki. PDF Poster

DBTest, 2012. Automated Physical Designers: What You See is (Not) What You Get. R. Borovica, I. Alagiannis and A. Ailamaki. PDF Slides Poster

SIGMOD, 2012. NoDB: Efficient Query Execution on Raw Data Files. I. Alagiannis, R. Borovica, M. Branco, S. Idreos and A. Ailamaki. PDF Slides Poster

DEB, 2011. Challenges and Opportunities in Self-Managing Scientific Databases. T. Heinis, M. Branco, I. Alagiannis, R. Borovica, F. Tauheed and A. Ailamaki. PDF


Introduction to programming (Java course) with Prof. Jamila Sam. EPFL, Fall 2014.

Programming I (C course) with Prof. Jean-Luc Desbiolles. EPFL, Spring 2014.

Project in informatics (C++ course) with Prof. Jamila Sam. EPFL, Fall 2013.

Computer-aided engineering II (C++ course) with Prof. Jamila Sam. EPFL, Spring 2013.

Introduction to object oriented programming (Java course) with Prof. Jamila Sam. EPFL, Fall 2012.

Computer-aided engineering (C++ course) with Prof. Jamila Sam. EPFL, Spring 2012.

Introduction to programming (Java course) with Prof. Jamila Sam. EPFL, Fall 2011.

Programming (Java course) with Prof. Thomas Lochmatter. EPFL, Spring 2011.


BC 241 (Batiment BC)
Station 14
CH-1015 Lausanne
Phone: +41 21 69 35684