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KNIME Analytics Platform vs ML Workspace

KNIME Analytics Platform

knime.com

ML Workspace

mltooling.org

Side by side

FigureKNIME Analytics PlatformML Workspace
Price from$19/moFree
Free planYesYes
Free trialYes—
Open source——
Web—Yes
WindowsYesYes
macOSYesYes
LinuxYesYes
Self-hosted—Yes
Plans published41
Spec score · Data Science Platforms8.1 (#8)8.3 (#7)
IntegrationsListed integrations include databases and warehouses such as PostgreSQL, Snowflake, Databricks, and BigQuery, plus cloud services, BI tools, and AI providers.Listed tools and integrations include Git, TensorBoard, Netdata, Jupyter, JupyterLab, and Visual Studio Code.
PurposeKNIME Analytics Platform creates visual workflows for data access, transformation, analysis, modeling, and visualization.ML Workspace is an all-in-one web-based IDE specialized for machine learning and data science.
SecurityKNIME describes security capabilities for user and asset management, data transfer, controlled deployment, monitoring, and logging.The documentation describes token or basic authentication options and configurable SSL/HTTPS support.

Plans

KNIME Analytics Platform

  • KNIME Analytics PlatformFree
  • Pro$19 a month
  • Team$99 a month
  • Business HubPriced on request

KNIME Analytics Platform pricing →

ML Workspace

  • ML WorkspaceFree

ML Workspace pricing →

In their own words

KNIME Analytics Platform

KNIME Analytics Platform is a free, open-source desktop application for building visual workflows to access, transform, analyze, model, and visualize data. It runs on Linux, macOS, and Windows and offers more than 300 connectors to data sources and services. Workflows can blend data of any size and type, then aggregate, sort, filter, and join it locally, in databases, or in distributed big-data environments. The platform includes interactive charts, spreadsheet task automation, machine-learning libraries, LLMs, and GenAI-assisted visualizations. Users can add Python, R, and JavaScript scripts or extend workflows with custom code. Listed integrations include PostgreSQL, Snowflake, Databricks, and BigQuery, along with cloud services, BI tools, and AI providers. KNIME describes security and governance capabilities such as workflow auditability and versioning, credential management, monitoring, logging, and data anonymization. It says processing takes place through KNIME Software on infrastructure chosen by the user. Downloading requires an email address and acceptance of terms and the Privacy Policy.

Visit knime.com

ML Workspace

ML Workspace is a self-deployed, web-based development environment for machine learning and data science. It brings browser-accessible Jupyter, JupyterLab, Visual Studio Code, and a Linux desktop GUI together, with libraries such as TensorFlow, PyTorch, Keras, and scikit-learn in its main image. Git-related tools include Ungit, Jupytext, nbdime, and a Jupyter extension for pushing notebooks. TensorBoard supports training monitoring, while Netdata and Glances cover hardware monitoring. The workspace can provide a remote runtime for Jupyter, VS Code, PyCharm, Colab, and Atom Hydrogen, typically through passwordless SSH, and can be accessed through a browser, SSH, or VNC. Image options include minimal, R, Spark, and GPU variants; the GPU flavor requires compatible Nvidia drivers and supports CUDA 11.2. Docker is required, with images deployable on Mac, Linux, and Windows. The project describes token or basic authentication and configurable SSL/HTTPS. It is designed for one user, and at least 2 CPUs and 500 MB of memory are recommended for stable use. The free plan costs nothing.

Visit mltooling.org