KNIME Analytics Platform
The open-source standard for data science, AI, and low-code workflow orchestration.
The notebook for reproducible research and collaborative data science.
Nextjournal is a high-performance, browser-based notebook environment designed specifically to solve the 'reproducibility crisis' in data science and scientific research. Unlike traditional Jupyter notebooks, Nextjournal encapsulates the entire stack—including the operating system, drivers, libraries, code, and data—within versioned Docker containers. This ensures that a notebook created today will execute with identical results in 2026 and beyond. Its technical architecture leverages a reactive execution engine and a content-addressed storage system, allowing for granular versioning of every change. The platform is notably polyglot, permitting users to run cells in Clojure, Python, R, and Julia within a single notebook session, facilitating seamless data hand-offs between languages. For 2026, Nextjournal has positioned itself as the premier environment for high-stakes AI research and enterprise-grade data transparency, offering 'Garden' for simplified hosting and a desktop application for local-first development. It bridges the gap between the flexibility of interactive coding and the rigor of software engineering best practices, making it indispensable for labs and data-heavy organizations requiring audit-trailed computations.
Captures the exact state of the file system and environment at every execution point using content-addressed storage.
The open-source standard for data science, AI, and low-code workflow orchestration.
The premier community-driven cloud environment for high-performance data science and machine learning.
The multi-user hub for Jupyter Notebooks, providing a centralized data science platform for teams and classrooms.
The operating system for modern AI and data science development.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A notebook engine that tracks dependencies between cells and updates them automatically when upstream data changes.
Allows multiple kernels to share data via the filesystem or memory within a single document flow.
Seamlessly offloads heavy computations to high-performance cloud instances while maintaining the frontend in the browser.
Transparently versions code using Git under the hood, allowing for branching and merging of notebooks.
A simplified deployment platform for turning notebooks into interactive web applications or API endpoints.
Users can import any Docker image to serve as the runtime environment, providing total control over system dependencies.
Journals require proofs that data results are repeatable by third parties.
Registry Updated:2/7/2026
Publish with a permanent URL for peer reviewers.
Distributed teams needing shared access to expensive GPU resources and consistent environments.
Merging a data cleaning script in Python with a statistical model in R.