Qbeast

Highly scalable multidimensional indexing system for NoSQL databases.

Institution:

Research Group:

Data-Driven Scientific Computing

Researcher/s:

Cesare Cugnasco

Website:

https://qbeast.io/

Description:

Qbeast is a highly scalable multidimensional indexing system for NoSQL databases. Qbeast supports queries with arbitray approximated precision and it is a good solution to store, visualize, explore and analyze large scientific simulations. It is also an efficient solutio to speedup machine learning algorithms. The current version of Qbeast is integrated with Apache Cassandra and thus, can be used through any regular Cassandra interface (from CQL, Hecuba or Apache Spark). If you are interested on testing Qbeast, please contact with Cesare Cugnasco (cesare.cugnasco@bsc.es)

Problem:

N/A

Solution:

N/A

Aplication areas:

N/A

Novelty:

N/A

Protection:

Proprietary

Target market:

N/A

Keywords:

big data

TRL: N/A

CRL: N/A

BRL: N/A

IPRL: N/A

TmRL: N/A

FRL: N/A

More information

if you want to know more about this project do not hesitate to contact us