KNIME

Enterprise features keep sensitive data safe and validate/monitor analytics and AI models

KNIME Analytics Platform is free and open source for personal use

Connects to 300+ data sources and services

Supports machine learning and GenAI analytics

KNIME offers an open ecosystem with free and open-source extensions that can be published on the KNIME Community Hub.

KNIME extensions can be developed in Java, Python, or both, integrating existing technology or implementing new capabilities as a no-code solution.

KNIME extensions integrate with data warehouses or lakes, third-party applications, and popular machine learning libraries.

Extensions are made available through the KNIME Analytics Platform.

KNIME's platform is used in hundreds of use cases across many areas in organizations, with extensions spanning industry-specific to scientific software integrations.

Experimental community extensions do not guarantee backwards compatibility.

KNIME provides a user community/forums for users needing additional help beyond the FAQ.

KNIME provides separate Developer FAQs for users developing their own nodes.

KNIME offers an interactive R language integration.

KNIME provides a (C)Python extension for Python scripting.

KNIME includes database connectivity nodes, including support for connecting to Microsoft Access databases.

KNIME runs on the Java Virtual Machine, as indicated by its configurable Java Heap Space settings.

Software is installed on an organization's choice of infrastructure, including local, cloud, or hybrid environments.

KNIME Software is comprised of KNIME Analytics Platform and KNIME Business Hub.

KNIME provides KNIME Community Teams, a SaaS option for small teams.

KNIME holds ISO 27001 certification, available on request.

KNIME follows a documented Secure Software Development Framework that includes security by design, static and dynamic code analysis, regular external penetration tests, vulnerability management, and monitoring with incident response.

Access data from 100+ sources including databases, big data platforms, AI model providers, cloud services, and file formats.

Supports AI model providers including OpenAI, Microsoft Azure OpenAI, Google AI Studio, Vertex AI, Anthropic Claude, IBM Watson, HuggingFace, DeepSeek, GPT4All, and Ollama.

Connects to major cloud platforms including Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, plus Microsoft 365 and Microsoft Fabric.

Integrates with relational, NoSQL, and cloud-native data warehouses including Oracle, Microsoft SQL Server, PostgreSQL, MySQL, MongoDB, Neo4j, Snowflake, Databricks, Google BigQuery, Amazon Redshift, and Amazon Athena.

Exports data and results to Business Intelligence and reporting tools including Tableau, Microsoft Power BI, Qlik, and TIBCO Spotfire.

KNIME Analytics Platform is a downloadable software product.

K-AI can generate a data app from an existing workflow by describing what to show, and it will create the components, add the views, and arrange the layout.

K-AI's build mode explores a workflow before making changes, inspecting relevant nodes, their configurations, and (with permission) their output data to understand data and structure first.

KNIME supports building AI workflows with Mistral's LLMs and embedding models.

The KNIME AI Extension includes dedicated Mistral nodes: Mistral AI Authenticator, Mistral AI LLM Selector, and Mistral AI Embedding Model Selector, with authentication, model selection, and configuration matching the Mistral API.

K-AI requests user permission for advanced actions that may be privacy-sensitive, time-consuming, or affect the workflow, with per-workflow allow/deny choices.