Comparing HL7 Interface Engines

Comparing HL7 Integration Engines

If you're knee-deep in HL7/FHIR messages and trying to choose an integration engine (or maybe replace your aging, and now expensive Mirth setup), you're in the right place. I’ve pulled together a comparison of the main players in the HL7 v2 integration space—from well-known giants to some refreshingly modern up-and-comers. Let’s break down who’s doing what, how easy they are to work with, and whether they’ll burn a hole in your wallet.

Integration Engine	License & Cost	Ease of Use	Standards & Connectivity	Scalability & Deployment	Strengths / Weaknesses
HL7 Soup Integration Host	Commercial subscription per workflow; free dev license. Lower cost than enterprise incumbents.	Very high – Intuitive GUI, drag-and-drop mapping, English HL7 translation. Minimal coding needed. Training/support included.	HL7 v2, FHIR, JSON, XML, CSV. MLLP (TCP), HTTP/S, file, DB, REST/SOAP. .NET scripting possible.	Moderate scalability. Runs on Windows, Azure, AWS, Docker. Secure TLS. No public HA/clustering info.	Strengths: Extremely user-friendly, embeddable UI, fast setup, low-cost. AI Designer. Weaknesses: Smaller vendor, limited large-scale presence. No Dicom support.
Infor Cloverleaf	Commercial, enterprise pricing per site or connection.	Medium – GUI exists, but often needs TCL scripting.	HL7 v2, HL7 v3, X12, DICOM, NCPDP. Broad protocol support.	Very high scalability; enterprise HA support. Unix/Linux or Windows.	Strengths: Trusted, powerful, highly scalable. Weaknesses: Expensive, steep learning curve, legacy tooling.
iNTERFACEWARE Iguana	Commercial, licensed per interface/channel. Higher-end pricing.	Medium – Lua scripting focus, minimal GUI mapping.	HL7 v2, JSON, XML, REST, DB, files. Highly flexible with code.	High scalability. Docker/cloud native. Windows/Linux.	Strengths: Fast, flexible, reliable for developers. Weaknesses: Requires coding, not beginner-friendly, costly.
Lyniate Corepoint	Commercial, enterprise subscription or perpetual.	High – Low-code GUI, drag-and-drop interface building.	HL7 v2, CCD, limited FHIR. Mostly GUI-based development.	Enterprise-grade, HA, Windows-only.	Strengths: Highly rated UI, excellent support. Weaknesses: Expensive, less flexible, not cloud-native.
Mirth Connect (NextGen)	Free open-source (MPL 2.0); enterprise version paid. OSS updates ending in 2025.	Medium – GUI-based, but JavaScript needed for mapping logic.	HL7 v2, X12, JSON, XML, REST, SOAP, DICOM.	Scalable via clustering. Cross-platform Java-based.	Strengths: Free, flexible, huge community. Weaknesses: Coding required, dated, cumbersome UI, questionable value as a commercial product.
Qvera Interface Engine (QIE)	Commercial; subscription or perpetual. Mid-range cost.	High – Web-based GUI, drag-and-drop + scripting.	HL7 v2, FHIR, HL7 v3, X12, DICOM, DB, JSON, XML.	High scalability, cloud-ready, HA supported.	Strengths: Versatile, modern UI, strong standards coverage. Weaknesses: Not open-source, smaller market share than top brands.

So... what do I choose?

Look, Mirth has had a good run—but let’s be honest, it's open source quality with a shiny new commercial license. I could justify my wasted time previously with the savings on licensing, but that's changed. It might be time for something new. That’s where HL7 Soup comes in.

It’s easy to use (like actually easy), has a drag-and-drop workflow builder, and reads HL7 in plain English. But what really makes it shine? Their AI-powered Mirth Channel Conversion Tool. You literally upload your Mirth channel, and—boom—it builds the equivalent HL7 Soup workflow for you. No rebuilds from scratch. No headaches.

Whether you're doing one-off lab results feeds or building out a whole interoperability stack, HL7 Soup is seriously worth a look. Especially if you want to spend less time writing glue code and more time doing, well... literally anything else.