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AVEVA™ Adapter for OPC UA

System requirements

  • Last UpdatedDec 16, 2025
  • 2 minute read

AVEVA Adapter for OPC UA is supported on a variety of platforms and processors. Install kits are available for the following platforms:

Operating System

Platform

Installation Kit

Processor(s)

Windows 11 Enterprise
Windows 10 Enterprise
Windows Server 2025
Windows Server 2022
Windows Server 2019

x64

AVEVA-Adapter-for-Opc-Ua-1.6.0.296-x64_.msi

Intel/AMD 64-bit processors

Debian 11,12
Ubuntu 22.04, 24.04

x64

AVEVA-Adapter-for-OPC-UA-1.6.0.296-x64_.deb

Intel/AMD 64-bit processors

Debian 11,12

ARM32

AVEVA-Adapter-for-OPC-UA-1.6.0.296-arm_.deb

ARM 32-bit processors

Debian 11,12
Ubuntu 22.04, 24.04

ARM64

AVEVA-Adapter-for-OPC-UA-1.6.0.296-arm64_.deb

ARM 64-bit processors

Alternatively, you can use tar.gz files with binaries to build your own custom installers or containers for Linux. For more information on installing the adapter with Docker containers, see Install using Docker.

PI Web API compatibility

This version of AVEVA Adapter for OPC UA is compatible with PI Web API 2021 and later.

AVEVA Adapter for OPC UA upgrade

If you are upgrading AVEVA Adapter for OPC UA from version 1.1 to 1.3 or newer and are sending data to PI Web API 2019, CONNECT data services, or both, read OPC UA Adapter - Upgrade from v1.1 to v1.2. This knowledge article contains important information about upgrade scenarios.

Performance metrics

A wide range of Linux and Windows based devices support AVEVA adapters, from small single board computers to large servers. Stream count and event throughput vary based on the device's hardware specification.

Performance guidelines for AVEVA adapters when running on typical small and large devices are as follows:

  • Small Devices - 4 Core CPU, 4 GB RAM (Raspberry Pi 4B equivalent). 10k events/sec, 10k streams total

  • Large Devices - 4 Core CPU, 8 GB RAM. 50k events/sec, 50k streams total

Actual performance of AVEVA adapters vary depending on different factors, such as the performance of data source, network latency, and hardware resource consumption by other applications on the device. We recommend solid state storage on the device to improve the performance, robustness, and reliability of the AVEVA adapter data buffering mechanism.

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