#InterSystems IRIS

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InterSystems IRIS is a Complete Data Platform
InterSystems IRIS gives you everything you need to capture, share, understand, and act upon your organization’s most valuable asset – your data.
As a complete platform, InterSystems IRIS eliminates the need to integrate multiple development technologies. Applications require less code, fewer system resources, and less maintenance.

Overview

Version 25.20.2 expands global availability, enhances Advanced Security flexibility, and widens Network Connect integrations. This release introduces support for additional regions, new application-aware security rules, and expanded connectivity options for critical InterSystems services.

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Overview

Version 25.23.2 delivers targeted improvements to the Advanced Security UI and further streamlines the upgrade and update workflows across InterSystems Cloud offerings. These changes focus on clarity, efficiency, and operational excellence.

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Overview

Version 25.24.1 delivers major enhancements to DNS capabilities, platform reliability, upgrade workflows, and developer experience. This release also includes key fixes and increases in platform limits to better support modern workloads.

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Overview

This release focuses on performance optimization, improved security synchronization, and enhanced network management. The FHIR Server has been upgraded to a new version and migrated to ARM64, delivering significantly better efficiency and throughput. Additionally, several improvements enhance resiliency, subscription management, and network visibility.

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Contestant

One objective of vectorization is to render unstructured text more machine-usable. Vector embeddings accomplish this by encoding the semantics of text as high-dimensional numeric vectors, which can be employed by advanced search algorithms (normally an approximate nearest neighbor algorithm like Hierarchical Navigable Small World). This not only improves our ability to interact with unstructured text programmatically but makes it searchable by context and by meaning beyond what is captured literally by keyword.

In this article I will walk through a simple vector search implementation that Kwabena Ayim-Aboagye and I fleshed out using embedded python in InterSystems IRIS for Health. I'll also dive a bit into how to use embedded python and dynamic SQL generally, and how to take advantage of vector search features offered natively through IRIS.

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