A better way to integrate data

Whenever information from different sources needs to be combined, the data structures supporting that information must first be related. This task, called data integration, is the biggest and most expensive challenge in IT today, accounting for over 40% of enterprise IT budgets.

Our technology performs data-integration tasks — such as querying, combining, and evolving databases — using category theory, a branch of mathematics that has already revolutionized several areas of computer science. Category theory gives us the theoretical guidance missing from current-generation data models (Relational, RDF/OWL, Graph, Key-Value, LINQ) and we have used it to build software for integrating data more quickly and more accurately than existing tools.

Our product consists of two parts:

  • AQL, an open-source query and data integration scripting scripting language that is hosted in an open-source integrated development environment (IDE).
  • A proprietary UI for increased productivity with AQL, currently under development.

AQL: an algebraic query language

The result of five years of research at MIT, AQL supports all of the operations needed to integrate and query data using category-theoretic principles. Its key benefits are:

AQL's key features are:

History

Categorical Informatics was spun out of the MIT Mathematics Department in the fall of 2015 and is supported by SBIR grants from the National Institute for Standards and Technology (NIST) and I-Corp grants from the National Science Foundation (NSF).

NIST NSF MIT