Introduction
Hi, I am Akira, the editor-in-chief of Data Without Code. If you have been following our tutorials, you have set up your workspace, learned how to download free templates from the KNIME Hub, and built some truly powerful automated reporting pipelines.
But as a DX manager, I know the exact fear that strikes every non-programmer when they see a pop-up notification saying: “A new version of KNIME Analytics Platform is available.”
Your first thought is probably: “If I click update, will it break all my automated reports?”
It is a valid fear. In the world of software, updates bring amazing new features, but they can also change how certain tools work. In this tutorial, I am going to share my foolproof best practices for upgrading KNIME so you can enjoy the latest features without ever risking your hard work.
Why You Should (and Shouldn’t) Rush to Upgrade
KNIME releases major updates twice a year (usually in summer and winter). These updates introduce a modernized user interface, faster processing speeds, and brand-new nodes.
However, if your company relies on a specific workflow to calculate payroll or consolidate regional sales data every Monday morning, do not upgrade immediately on a Friday afternoon. Always plan your upgrades during a quiet period so you have time to test your workflows.
Best Practice #1: Back Up Your Entire Workspace Folder
Before you even think about downloading the new version, you must back up your workspace.
Do you remember when we first discussed how to install KNIME and set up your workspace? Your workspace is just a folder on your computer. The absolute easiest way to secure your work is to simply copy that entire folder and paste it somewhere safe (like an external hard drive or a different cloud folder) and rename it to something like KNIME_Workspace_Backup_2026.
If anything goes wrong with the new version, your raw data and logic are perfectly safe in that backup folder.
Best Practice #2: Export Your Most Critical Workflows
While backing up the folder is great, I always take one extra step for my “Mission Critical” automations. I export them individually as .knwf files.
If you forgot how to do this, check out my previous guide on how to safely export and share KNIME workflows. Saving your top three most important workflows to your desktop ensures you have a clean, isolated template ready to import into the new version.
Best Practice #3: Install Side-by-Side (Do Not Overwrite)
This is the ultimate DX manager secret. When you download a major new version of KNIME (for example, moving from version 4.x to 5.x), do not uninstall the old version.
KNIME allows you to install multiple versions on the same computer. Simply download the new installer and save it in a slightly different folder (e.g., C:\Program Files\KNIME_v5). When you launch the new version, point it to your existing workspace.
By keeping the old version installed, you have a perfect safety net. If a workflow fails in the new version, you can simply close it, open the old KNIME, and run your report exactly as you always have.
Best Practice #4: Update Your Extensions
When you upgrade the core KNIME platform, your extensions (like Google Sheets connectors or advanced machine learning nodes) might need an update too. Once you open the new version, immediately go to File > Update KNIME… to ensure all your extra tools are compatible with the new engine.
If you are missing tools, you can simply reinstall your extensions using the built-in menu.
Conclusion: Welcome to the Next Phase
By following these four simple rules, you completely eliminate the risk of losing your automated pipelines. You can update your software with total confidence.
And with that, you have officially graduated from the KNIME Basics module! You now understand the interface, the nodes, the Hub, and how to maintain your workspace like a true IT professional.
It is time to get our hands dirty with real data engineering. In our next module, we are diving deep into Data Prep & ETL. Are you tired of manually separating first names from last names in messy Excel files? Join me in our next tutorial: How to split text into columns in KNIME using the Cell Splitter node!
