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TECH - MACHINE LEARNING

InterSystems IRIS Community Edition

InterSystems

InterSystems IRIS® is a comprehensive cloud data platform powering large-scale, mission-critical applications worldwide.

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Product Description

Overview
InterSystems IRIS® is a cloud-native, enterprise-grade data platform used worldwide to power large-scale, mission-critical systems. It is designed for high-throughput environments that require real-time transaction processing alongside advanced analytics such as analytic SQL, business rules, and machine learning. By combining SQL and NoSQL database management, data integration, application integration, and analytics in a single platform, InterSystems IRIS accelerates delivery, reduces operational complexity, and eliminates the need to move or duplicate data across environments.

The platform enables concurrent transactional and analytical processing and supports multiple fully synchronized data models, including relational, hierarchical, object, and document. It also delivers a comprehensive interoperability layer for connecting disparate systems and data sources, along with rich analytics for both batch and real-time workloads.

InterSystems IRIS provides an open analytics framework that allows organizations to integrate advanced analytics built in external tools, as well as flexible deployment options that support cloud, on-premises, or hybrid architectures. Built on a unified architecture, it supports a wide range of use cases such as business and customer 360, risk and compliance, supply chain visibility, IT/OT convergence, and predictive and prescriptive analytics.

Highlights

  • High-performance single engine optimized for concurrent transactional and analytical workloads with efficient resource usage

  • Native multi-model data support, including relational, document, object, key-value, and multidimensional models

  • Embedded analytics with BI, text analytics, and predictive modeling, featuring an integrated Python engine and high-performance connectors to leading analytics tools

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