VectorWise is a spin-off from the renowned CWI institute in Amsterdam. Its founders bring a long history of scientific innovation, demonstrated with the MonetDB project.

VectorWise, while incorporating many ideas from MonetDB, is a completely new database engine, designed from scratch with the goal of combining the best features of traditional database architectures and MonetDB and overcome limitations of both. Our technology is based on the research performed at the CWI database group under the codename MonetDB/X100.

The architecture of the X100 system is described in the Data Engineering Bulletin 2005 article. It proposes numerous technological innovations improving the performance of database engines. The novel vectorized in-cache model of query execution (see the CIDR 2005 publication) effectively eliminates many of the overheads found in the traditional solutions and manages to fully utilize the performance potential of modern CPUs, achieving dramatic performance improvement for in-memory processing. Two techniques are used to scale this performance to disk-resident data sets. The concept of lightweight in-cache compression (see the ICDE 2006 article) allows trading some processor time for an increased data delivery bandwidth. Additionally, cooperative scans (see the VLDB 2007 publication) dynamically schedule query activity and I/O operations to amortize the cost of disk access among multiple queries. As a result, X100 has been shown to provide very high performance both for in-memory and disk-based database tasks, as well as in large-scale information retrieval scenarios (see our VLDB Journal 2008 article). Additionally, this technology became a foundation for various hardware-conscious database techniques, presented in a series of DAMON papers (2006, 2007, and 2008).

VectorWise continues performing cutting-edge research in collaboration with CWI and other academic institutions.