Application Name | Developer | Made with | Rating | Last updated | Views | Installs |
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MDX2JSONRESTful web api for MDX to JSON transformation (plus JSONP and XML/A) for InterSystems Caché. Also provides information about DeepSee objects. | E | IPM | 4.5 (2) | 08 Sep, 2025 | ||
CubeEventMonitorTool for monitoring BI cube events and build errors | S | Docker IPM | 4.0 (1) | 15 Jul, 2025 | ||
InterSystems Ideas Waiting to be ImplementedImplement IRIS connector for Airbyte data integration engineAirbyte is an open-source data integration platform that allows users to sync data from different sources to various destinations. Its architecture is modular and it relies on the use of connectors for each source or destination. Every connector has the task of understanding, extracting, and writing data from or to a specific system. https://airbyte.com/connectors The reasons for implementing a connector to IRIS for Airbyte include: * Real-time Data Movement: If you want to move data in real-time (or near-real-time) from IRIS to other platforms (or vice-versa), a dedicated connector in Airbyte can facilitate that. * Ease of Use: With an Airbyte connector, users can easily set up and manage data integrations without having to write custom code. This is particularly useful for teams without extensive development resources. * Scalability: Airbyte's architecture supports scalable data integration. As your data grows in IRIS or other platforms, Airbyte can handle the increased load. * Customization: Every organization's data needs are unique. With an open-source platform like Airbyte, organizations have the flexibility to customize the IRIS connector as per their specific needs. * Community Support: As more organizations use and contribute to the Airbyte connector ecosystem, the connectors, including the one for IRIS, will benefit from community-driven enhancements, bug fixes, and best practices. In conclusion, implementing a connector to IRIS for Airbyte can significantly simplify and enhance the process of integrating InterSystems IRIS with other data platforms and tools, enabling organizations to gain more value from their data assets. Airbyte offers cloud or self-managed solutions, as well as open-source and enterprise. D 5Votes2Comments | ||||||
PivotToPowerBIView extracted data from IRIS BI cubes in Power BI | P | Docker IPM | 0.0 (0) | 22 Jun, 2025 | ||
ReadyForActionDemo for "Demos and Drinks" at InterSystems READY 2025 | P | Docker Python | 5.0 (1) | 20 Jun, 2025 | ||
![]() AnalyzeThisEasily transform a CSV file/Table/SQL query into a personalized preview of InterSystems IRIS BI | P | Docker IPM | 5.0 (3) | 20 Jun, 2025 | ||
![]() ThirdPartyChartPortletsUse third-party charting libraries inside of Dashboards | P | Docker IPM | 4.5 (1) | 20 Jun, 2025 | ||
CustomCubeActionManagerEasily manage InterSystems IRIS BI custom cube actions | P | Docker IPM | 0.0 (0) | 06 Jun, 2025 | ||
![]() PivotSubscriptionsSubscribe to Pivot Tables in InterSystems IRIS Business Intelligence to receive scheduled emails | P | Docker IPM | 0.0 (0) | 14 May, 2025 | ||
iris-analytics-templateBasic template for IRIS Analytics solutions | Docker IPM | 5.0 (2) | 13 Aug, 2024 | |||
samples-bi-demoDemo of InterSystems IRIS BI cubes, pivots and dashboards in DSW | Docker IPM | 4.5 (1) | 14 Jun, 2024 | |||
![]() iris-analytics-packageThis project has the intention to show a basic approach using the Analytics capabilities of InterSystems IRIS | Docker IPM | 5.0 (1) | 25 Mar, 2024 | |||
Samples-BIProvides sample data for use with InterSystems IRIS Business Intelligence, as well as fully developed sample BI models and dashboards. | Docker IPM | 5.0 (1) | 25 Mar, 2024 | |||
WidgetsDirectorA sample IRIS Backend app to implement a REST API for a helpdesk | C | Docker IPM | 3.8 (3) | 23 Jan, 2024 | ||
![]() Intersystems IRIS platform queue trend monitoring componentIntersystems IRIS platform queue trend monitoring component | Y | IPM | 3.5 (2) | 03 Feb, 2023 | ||
![]() iris-analytics-datastudioGoogle DataStudio connector to InterSystems IRIS Analytics (DeepSee) | 4.0 (1) | 09 Sep, 2021 | ||||
Reducing Readmission Risks with Realtime MLPatient Readmissions are said to be the Hello World of Machine Learning in Healthcare. We use this problem to show how IRIS can be used to safely build and operationalize ML models for real time predictions and how this can be integrated into a random application. | A | Docker ML ML | 3.5 (1) | 29 Jan, 2020 | ||
DeepSeeButtonsTool for analyzing your DeepSee Environment | P | 4.0 (1) | 12 Dec, 2019 | |||
DSW ReportsAddon for DeepSee Web which provides online reports and PDF emailing reports from InterSystems DeepSee dashboards | S | 0.0 (0) | 11 Dec, 2019 |