Is there any way of saving a representation of the results of a query created in the Message Viewer to a file - most obviously CSV.

We are reasonably adept at creating queries. We'd like to be able to send the output to a file, rather than resorting to cut'n'pasting from the message viewer window...

Is this possible? (on any version of Ensemble/Iris?)

Desired output to file something like:

I need to implement a retry policy for an incoming message queue containing thousands of relatively small messages.

Successfully processed messages should be immediately removed from the queue.

Hello everyone,

I’m facing issues with replicating data from my Caché 2016 database to a PostgreSQL database. I need to handle around 300 data updates per minute, and whenever certain tables are modified, those changes must be reflected in other databases.

So far, I’ve tried various approaches, including:

I recently had to refresh my knowledge of the HealthShare EMPI module and since I've been tinkering with IRIS's vector storage and search functionalities for a while I just had to add 1 + 1.

For those of you who are not familiar with EMPI functionality here's a little introduction:

Enterprise Master Patient Index

In general, all EMPIs work in a very similar way, ingesting information, normalizing it and comparing it with the data already present in their system. Well, in the case of HealthShare's EMPI, this process is known as NICE:

What is the recommended library for converting documents to pdf. Any suggestions welcome has anyone out there had a use case where they had to convert documents to pdf .What worked for them .I have asked WRC for the best practice and they have recommended that may be a sale engineer might have an answer to this .

Hi Community!

We're happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Open Source and Proprietary LLMs

https://www.youtube.com/embed/-LAzjc5MCac
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Hi everyone,

It's me again😁. As usual I would like to share something I study recently, and today, I would like to share about the document DB😁.

InterSystems has released new point updates to resolve a defect affecting the most recent prior versions of 2025.1.0, 2024.1.4, 2023.1.6, and 2022.1.7, for the following supported product lines:

Hi Developers!

Here're the technology bonuses for the InterSystems AI Programming Contest: Vector Search, GenAI and AI Agents that will give you extra points in the voting:

• Agent AI solution - 5
• Vector Search usage - 4
• Embedded Python - 3
• LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
• IntegratedML usage - 3
• Docker container usage - 2
• ZPM Package deployment - 2
• Online Demo - 2
• Implement InterSystems Community Idea - 4
• Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
• First Article on Developer Community - 2
• Second Article On DC - 1
• First Time Contribution - 3
• Video on YouTube - 3
• Suggest a new idea - 1

See the details below.

Hey Community!

We're happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Energy Consumption for AI

https://www.youtube.com/embed/o99hGFoCeuU
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Hi Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ InterSystems Package Manager @ Global Summit 2024

https://www.youtube.com/embed/yVPsOp5AZfU
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Hi,

After converting from Ensemble 2018 to IRIS 2024 I noticed that HTML tag is not recognized?

I just copied & pasted this same from Ensemble to IRIS and in Ensemble looks fine!?

Thanks

If you want to know if a class about a topic already exists asking a simple natural language question, it is possible now. Download and run the application https://openexchange.intersystems.com/package/langchain-iris-tool to know all about your project classes in a Chat.

Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability: