KNIME for Databricks Users
Access Databricks data, analyze it, and get meaningful insights with a low-code/no-code interface.
Combine the Databricks Data Intelligence Platform with KNIME’s low-code/no-code analytics
Connect with data stored on your Databricks Data Intelligence Platform, without dependence on data engineers.
Equip all data workers to build visual, low-code/no-code analytic workflows powered by Databricks’ resources.
Make analyses available as interactive data apps to users across the organization.
Why KNIME and Databricks to speed up insights
Access Databricks data and clusters
- Connect to all your data on Databricks through dedicated nodes, without waiting for data engineering assistance.
- Manipulate data or execute Spark jobs while pushing all computation processes down into your Databricks cluster.
- Ensure that data remains within your Databricks environment, minimizing data movement and maximizing data security.
- Save egress fees by customizing workflows to use as much Databricks processing as possible.
Empower more users to derive insights from Databricks data
- Enable users of all skill levels to analyze Databricks data with an intuitive low-code/no-code interface and a GenAI assistant.
- Give advanced users the flexibility to script custom Spark jobs that execute directly on Databricks clusters using PySpark, Java, or SQL.
- Choose from a wide range of analytic techniques and access popular machine learning libraries, including large language models (LLMs).
- Share your analysis as components with other teams for reuse
- Accelerate data science upskilling with working blueprints and guidance from the KNIME Community.
Broadcast your findings via data apps, reports, and REST APIs
- Increase data literacy and data-driven decision making across the business by sharing analyses as data apps, REST APIs, or reports.
- Build data apps with a no-code, low-code framework and put complex analyses into the hands of end users.
Transform raw data into insights within a unified environment
- Connect to data from Databricks and other sources in a unified environment.
- Build, train, and deploy models enterprise-wide using the same intuitive environment.
- Eliminate the challenges of disconnected technologies with a platform that takes you from analytics creation to production in a single environment.
