Compare to Relational Databases

When it comes to databases, one size doesn’t fit all.

SciDB is a computational database – not a data warehouse, not a business-intelligence database, and not a transactional database.

Conventional databases have the wrong data model for complex analytics. Machine-generated data, scientific data, and data with spatial or temporal ordering do not fit neatly into a relational table, leading to inefficient storage and poor analytics performance.

And conventional databases are missing critical functionality like data versioning that support reproducing and auditing results.

SciDB’s multi-dimensional array data model is a natural match for complex data like genetic sequencing data, sensor data, financial data and geospatial data. And since SciDB is an all-in-one database and analytics platform, you don’t have to extract, reformat, and export your data to a standalone math package.

SciDB is designed from the ground up for large-scale complex analytics:

• Provides automated, transparent support for massively distributed data sets.
• Accelerates array operations by 10-100x because data is stored natively in an array format.
• Natively integrates complex analytics directly with data management, supporting ad-hoc analytics at scale.
• Supports reproducing and auditing of results because data is never overwritten, only updated.