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Show HN: KelpMesh – pure SQL data transformation, no Jinja required

KelpMesh is an open-source alternative to dbt that uses pure SQL instead of Jinja-templated SQL.

No Jinja. No macros. Just SQL.

-- This is valid KelpMesh. Dependencies resolved by parsing the AST.
SELECT customer_id, SUM(amount) AS total FROM orders GROUP BY 1

Why this matters: dbt forced analysts to learn Jinja templating embedded inside SQL. This breaks IDE intellisense, AI coding assistants (Copilot/Cursor can't parse Jinja-templated SQL), SQL linters, and code review. Every {{ ref('model') }} and {{ config(...) }} block makes the SQL harder to read, review, and maintain.

KelpMesh's approach: dependency resolution via AST parsing. Your SQL is valid, portable SQL. Nothing more.

What ships in 0.2:

  • Column-level lineage (free, not enterprise-locked)
  • 6 warehouses: DuckDB, Snowflake, BigQuery, Postgres, Databricks, Microsoft Fabric
  • Security suite: audit logging, RLS, column masking, data classification, PII erasure, secrets scanning, transparent encryption
  • dbt migration: KelpMesh import ./dbt-project --output ./KelpMesh-project
  • No telemetry (zero phone-home, enforced at code level)
  • 27 CLI commands
pip install KelpMesh
kelpmesh init my_project
kelpmesh run

License: Apache 2.0

https://github.com/RoyPulseAI/kelpmesh