# slothflowlabs/duckle

Open-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.

Repository: https://github.com/slothflowlabs/duckle
Canonical: https://ross.abutalabs.com/products/duckle
Homepage: https://duckle.org/
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: data-engineering, data-integration, data-pipeline, data-quality, duckdb, elt, etl, cdc, connectors, dbt, no-code, data-transformation, reverse-etl, data-orchestration, lakehouse, low-code, mcp, open-source, self-hosted, kubernetes
Last push: 2026-09-02T16:57:18+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 100, longevity 7
- inputs: {"age_days": 104, "days_push": 0, "days_rel": 3, "gap_med": 1.5, "n_releases_24m": 31}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1262, forks 94 (observed 2026-09-03T02:15:17.945872+00:00)

## What it is
Duckle is an open-source ETL/ELT platform built on DuckDB that you self-host on your own servers or cloud, with a visual no-code/low-code canvas, SQL, or Python authoring. It ships 380+ components (sources, transforms, sinks, quality validators), CDC, dbt support, reverse ETL, lineage, scheduling, and an MCP server for AI agents, with no vendor cloud or per-row billing.

## Use cases
- sync postgres data to parquet files on a schedule
- build etl pipelines without writing code
- run change data capture from mysql to a warehouse
- self-hosted alternative to fivetran or airbyte
- clean and dedupe data before feeding an llm or rag pipeline
- run dbt models on duckdb locally
- move data between s3, snowflake, and saas apis
- let ai agents trigger data pipelines via mcp

## When to choose
- you want pipelines on your own infrastructure with no vendor cloud or per-row billing
- you need a visual canvas plus SQL transparency (generated SQL on every node)
- you want a single DuckDB engine for local-speed transforms across 180+ connectors
- you need CDC, incremental loads, data quality validators, and reverse ETL in one tool
- you want pipelines as single files versioned in git

## When to avoid
- you need a fully managed cloud ETL service with zero infrastructure
- you require connectors still on the roadmap (e.g. IBM DB2, Chroma, LanceDB)
- your team depends on a mature, long-proven enterprise platform rather than a beta-stage tool
- you need streaming real-time processing rather than batch/scheduled pipelines

## Facets
- artifact type: application
- maturity: active
- function: etl, data-science, workflow-automation, scheduling, rag, mcp, data-visualization, developer-tools
- domain: data-science, analytics, databases, self-hosted
- platform: windows, self-hosted, cross-platform
- tags: duckdb, elt, cdc, dbt, reverse-etl, data-quality, no-code, low-code, connectors, lakehouse, data-orchestration, lineage, visual-pipeline-editor, tauri, data-engineering, automation, macos, linux, docker, kubernetes, desktop

## Member repositories
- slothflowlabs/duckle (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:17.945872+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:22:01.081443+00:00, confidence not recorded.
  - readme: https://github.com/slothflowlabs/duckle (fetched 2026-09-03T02:15:17.945872+00:00, sha db2281238d68)
  - homepage: https://duckle.org/ (fetched 2026-08-29T12:21:25.111232+00:00, sha 09f4ed1e1fe7)
  - site_page: https://duckle.org/docs/components.html (fetched 2026-08-29T12:21:25.114348+00:00, sha 7de688f4d33b)
  - site_page: https://duckle.org/docs/automation.html (fetched 2026-08-29T12:21:25.116538+00:00, sha e05658e46f8d)
  - site_page: https://duckle.org/docs/index.html (fetched 2026-08-29T12:21:25.118337+00:00, sha d96a0848a95a)
  - site_page: https://duckle.org/docs/learn.html (fetched 2026-08-29T12:21:25.120143+00:00, sha f849e575e179)
  - site_page: https://duckle.org/docs/integrations.html (fetched 2026-08-29T12:21:25.121888+00:00, sha 0555d3253a7c)
  - site_page: https://duckle.org/docs/ai-duckie.html (fetched 2026-08-29T12:21:25.155994+00:00, sha 6682df30fb2d)
  - site_page: https://duckle.org/docs/getting-started.html (fetched 2026-08-29T12:21:25.203553+00:00, sha 7da3c07e3ad7)
- Data as of 2026-08-30T08:39:29.467469+00:00.