New Technology for Big Analytics

Paradigm4′s open-source analytical database provides advanced mathematical and technical computing functionality for use with massive data sets along with many capabilities unavailable from conventional relational databases or technical computing software packages.

Build on our hard-earned experience and expertise

Mike Stonebraker, renowned database researcher and entrepreneur, along with a team of seasoned database developers, have created this next-generation analytical database to meet the requirements and wish lists we’ve been hearing from scientists, data scientists, bioinformaticians, analysts, and researchers.

No need for proprietary hardware

Paradigm4′s shared-nothing, massively parallel processing (MPP) distributed database runs on 10s to 1000s of commodity-hardware nodes in a cloud or private grid.  No need for expensive high-performance computers or costly database appliances.

Native support for array operations

Paradigm4 accelerates array operations — the basis for linear algebra operation like covariance and SVD — by 10-100x because data is stored natively in an array format.  Analytics operations scale seamlessly to billions of datapoints without rewriting your analytical code or manually distributing your data.

More compact storage for both sparse and dense data

Data storage is significantly more compact and data access is faster with Paradigm4′s unique physical storage model for both sparse and dense data.  Moreover, indices are calculated, not stored, further reducing memory requirements and supporting ad-hoc queries without extensive a priori database tuning. Clustering and neighborhood operations on semantically-related data are fast because data is partitioned in N dimensions, not just 1.

Embed advanced analytics directly in queries

Access and analyze data through a SQL-like Array Query Language (AQL), or an Array Functional Language (AFL). Learn about the AQL and AFL query languages.

Move beyond the elephants

Learn more how Paradigm4 compares to relational databases, map-reduce systems, analytical software packages, and NoSQL systems.