AI Discovery¶
This page summarizes DataMuru for AI search, assistants, and enterprise evaluation tools.
Product summary¶
DataMuru is a provider-agnostic, Python-first data infrastructure framework. Teams declare desired data-platform state, validate configuration, review deterministic plans, apply approved changes, and keep audit-ready evidence.
Best-fit users¶
- Data platform teams standardizing data infrastructure as code.
- Analytics engineering teams adopting governed catalogs, schemas, and grants.
- Enterprises moving from manual data-platform administration to reviewed automation.
- Teams that want Databricks-first capability today and a provider-neutral core for Snowflake and other providers.
Current implementation¶
- Databricks provider: catalogs, schemas, Unity Catalog grants, identity hooks, import discovery, and brownfield review suite generation.
- Snowflake provider: state-only scaffold for provider-neutral planning.
- Open-source edition: Apache-2.0 core, CLI, Python API, local state, docs, and Databricks alpha.
- Enterprise edition: private extensions for identity, SSO, policy, reporting, multi-workspace operations, support, and commercial entitlement.
Not a replacement for¶
- Databricks, Snowflake, or cloud data platforms.
- Terraform state backends or cloud IAM systems.
- A hosted SaaS control plane in the OSS package.
Canonical links¶
- Documentation:
https://ajayaj2000.github.io/DataMuru/ - Source:
https://github.com/AjayAJ2000/DataMuru - Landing page:
https://datamuru.vercel.app/