Research Area: Big Data Management Technologies
Our work is concentrated on the evaluation and optimization of
- Operational data stores that allow flexible schemas
- Big Data management and analytical platforms (Hadoop, Spark, etc …)
- Complex distributed storage and processing architectures
- Big Data Benchmarks
We are interested to benchmark new software platforms for storing and processing massive amounts of data and for analytics beyond what conventional relational systems can do. We are interested to test such systems against domain specific workloads to perform data clustering, predictive modeling, and complex statistics. In addition, we are investigating graph-based DBMSes for social-network-style analysis.
We are also interested to test new innovative data processing systems that facilitate rapid processing and ingest of data streams. One of the key technical challenges of Big Data is “Data Velocity“, that requires data ingest and data conditioning at high rates, including the abilities to aggregate data at high speeds and load it into database management systems.