CompDB · The Computational Database for Real World Awareness

Two major hardware trends have a significant impact on the architecture of database management systems (DBMSs): First, mainmemory sizes continue to grow significantly. Machines with 1TB of main memory and more are readily available at a relatively lowprice. Second, the number of cores in a system continues to grow, from currently 64 and more to hundreds in the near future. This trend offers radically new opportunities for both business and science. It promises to allow for information-at-your-fingertips, i.e., large volumes of data can beanalyzed and deeply explored online, in parallel to regular transaction processing. Currently, deep data exploration is performedoutside of the database system which necessitates huge data transfers. This impedes the processing such that real-time interactiveexploration is impossible. These new hardware capabilities now allow to build a true computational database system that integrates deep exploration functionality at the sourceof the data. This will lead to a drastic shift in how users interact with data, as for the first time interactive data explorationbecomes possible at a massive scale.Unfortunately, traditional DBMSs are simply not capable to tackle these new challenges.Traditional techniques like interpreted code execution for query processing become a severe bottleneck in the presence ofsuch massive parallelism, causing poor utilization of the hardware. I pursue a radically different approach: Instead of adapting thetraditional, disk-based approaches, I am integrating a new just-in-time compilation framework into the in-memory database thatdirectly exploits the abundant, parallel hardware for large-scale data processing and exploration. By explicitly utilizingcores, I will be able to build a powerful computational database engine that scales the entire spectrum of data processing - fromtransactional to analytical to exploration workflows - far beyond traditional architectures.