Kamu
6.9#4 in data fabric softwareFree planFree planWebAPILinuxmacOS
Visit| Fact | Kamu | One Data |
|---|---|---|
| Company | The site identifies the company as Kamu Data Inc. | One Data says it was founded in Passau, Germany, in 2013 and lists offices in Munich, Passau, Frankfurt, and Berlin. |
| Deployment | Kamu Node is a scalable server implementation of ODF, deployable as Kubernetes applications in a distributed environment. | One Data can run in a customer’s AWS or Azure cloud, on premises, or hosted by One Data; on-premises deployment depends on Kubernetes and infrastructure requirements. |
| Integrations | Kamu says it integrates Spark, Flink, Arroyo, and Datafusion as plugins, allowing different engines in one pipeline. | The platform page names Databricks, Snowflake, Tableau, Power BI, and PostgreSQL as examples of compatible data platforms and tools. |
| Security | The CLI installation guide warns that sudo-less Docker access can expose the filesystem with root privileges and recommends rootless Podman as an alternative. | One Data states that the company is ISO 27001 certified and TISAX-assessed, and that the software supports SSO and multi-factor authentication and is GDPR compliant with European data residency available. |
| Support | The maker directs users to GitHub issues or Discord for feedback and questions. | One Data describes support ranging from guided self-service to fully managed assistance, including setup and ongoing updates. |
| What it does | Kamu CLI is a command-line tool for managing and verifiably processing dynamic structured data. | One Data is a modular data management platform that adds structure, business context, and governance to enterprise data for reporting, analytics, and AI. |
No prices published.
Kamu may suit teams exchanging data between independent parties or handling low-to-moderate-frequency data where traceability and protection from malicious actors matter. It is not described as a good fit for high-frequency, high-volume workloads.
The platform is for enterprise data engineers, stewards, business analysts, AI and analytics teams, and CDOs or leadership. It may suit organizations seeking data governance, lineage, and managed data-product access across systems.