RAPID & FAIR data access from the ground up.
SciDB rapidly serves up the selected data of interest because it preserves the logical structure and co-locality of data in its native data storage format. It’s what makes SciDB a scientific data management system at its core and differentiates it.
SciDB runs analytics, signal processing, image processing, and machine-learning elastically in parallel on data distributed across a cluster…on any cloud or on-premises.
With Burst-Mode, the elastic cluster automatically expands to thousands of CPU cores to handle large compute tasks, while leveraging cheaply-available “spot” capacity – maximizing calculation speed and minimizing total compute cost.
Familiar interfaces for scientific analysis
Data scientists and bioinformatics researchers work in R and Python, so we made R and Python the query languages for SciDB. SciDB brings the computation to the data, running math and machine-learning functions from any library on the data in its native data format. Selected data and/or the results of large computations can be exported to R or Python for further analysis and visualization. Workflows are captured and documented in R markdown and Jupyter notebooks. REST APIs provide an interoperable, HTTP interface.
Apps, not Ecosystems
Scientists also told us they wanted higher-level, use-case focused solutions, not just workspaces which require them to assemble their own
Multiple users can load, read, and write data in a secure, transactionally safe manner as data operations are guaranteed to be atomic and consistent (ACID compliant).
Together SciDB and REVEAL™ provide an AGILE SCIENCE™ platform for expediting translational research.
For a deeper technology dive, contact us.
