Skip to content
KNIME Documentation
Main Navigation Get startedBuildWork with KnimeAccount and adminRelease notesDeveloper tools
Community Hub
DevelopersKnime
Sidebar Navigation

Getting Started

Installation

User Guide

Release Notes

Install Extensions

Building Workflows

Components

Flow Control

Expressions

File Handling

Deployment

Integrated Deployment

Workflow Invocation

Best Practices

Advanced Features

AI Extension

Get Started

Build an Agent

Inject context with RAG

LLM Providers

Tutorials

Summarize product reviews

Product FAQ assistant

Restaurant agent

Your first local agent

Task extractor

Reporting

Kerberos

Extensions

Database

Overview

Tutorials

Read and filter data from a database

Write a transformed dataset to a database

Concepts

Ports and Sessions

Query Generation

Type Mapping

Deprecated Framework

Connecting

Connect: Dedicated Node

Connect: File-Based Database

Connect: Generic DB Connector

Register a JDBC Driver

Install Third-Party Driver Plug-in

Drivers on Hub and Server

Kerberos Constrained Delegation

Reading and Transforming

Read Data

Transform Data Visually

Run a Custom SQL Query

Parameterize a Query

Writing and Modifying

Insert, Update, or Merge

Delete Rows

Bulk Load Data

Create and Remove Tables

Use Transactions

Reference

Connector Node Settings

JDBC Driver Reference

Deprecated Node Mapping

Migrate Deprecated Workflows

Python

Overview

Tutorials

Python Scripting Quickstart

Data App Development Using Plotly

Data Processing

K-AI Scripting Assistant

Data Type Conversion

Batch Processing

Jupyter Integration

Environment Management

Pixi Configuration

Dependency Management

Environment Persistence

Channel Mirrors & Air-Gapped Setups

Conda Migration

Alternative Configurations

Conda and Miniforge Setup

Conda Environment Propagation

Manual Python Configuration

Legacy Node Migration

Concepts

Pixi Backend Architecture

Storage Logic

Python Environments on Executors

Reference

Python Scripting API

Bundled Packages

Executor and Hub Configuration

Troubleshooting Guide

API Reference

Inputs and outputs

Classes

Views

Utility functions

R

Deep Learning

Snowflake

Google Cloud

Azure

AWS

Big Data

Big Data Admin

Big Data Secured Cluster

Databricks

Microsoft Fabric

Power BI

Tableau

Report Designer

H2O

Changelogs

Version 5.12

Version 5.11

Version 5.10

Version 5.9

Version 5.8

Version 5.7

Version 5.6

Version 5.5

Version 5.3

Extensions

Deprecated database framework ​

KNIME Analytics Platform 5.3.0 introduced a deprecation mechanism for older JDBC drivers. This page explains what deprecation means, how deprecated drivers behave, and when you should act.

Background ​

The KNIME Database Extension replaced an older database framework that used different node names (for example, Database Reader instead of DB Query Reader) and a separate driver registration page. The older framework is now deprecated. Existing workflows that use deprecated nodes continue to work, but KNIME recommends migrating them to the current framework.

For the full list of deprecated nodes and their replacements, see Deprecated node mapping.

How deprecated drivers work ​

Older JDBC driver versions become deprecated when the database vendor no longer supports them or when they contain known security vulnerabilities. KNIME marks deprecated drivers clearly in the node dialog. If a workflow selects a deprecated driver, the workflow editor displays a warning.

Deprecated driver in node dialogWarning in workflow editor
Deprecated driver dialogDeprecated driver warning

After a deprecation period, KNIME removes deprecated drivers from the platform. If a workflow still references a removed driver, KNIME displays an exception that identifies the extension to install to restore access.

Reinstalling a removed driver ​

To install a deprecated driver extension:

  1. Open the installation dialog as described in the KNIME Analytics Platform Installation Guide.
  2. Deselect Group items by category.
  3. Search for the extension name shown in the exception.
  4. Select the extension and install it.
  5. Restart KNIME Analytics Platform.

The example below shows the deprecated Snowflake driver being reinstalled.

Installing a deprecated driver extension

Use cases ​

You opened a workflow with a deprecation warning ​

The workflow still executes. Review the warning, check whether a supported driver is available for your database, and update the connector node to use the current driver.

A driver was removed and the workflow fails ​

Install the deprecated driver extension as described above, or migrate the workflow to use a current connector node with a supported driver.

Next steps ​

  • Migrate deprecated database workflows
  • Register a JDBC driver

Related pages ​

  • Deprecated node mapping
  • DB ports and sessions
Pager
Next pageInstallation