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. observed · 2026-09-03
Health v2 · maintenance only
81/100
- Activity 100
- Release rhythm 100
- Longevity 7
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 1.5
- age_days: 104
- days_rel: 3
- days_push: 0
- n_releases_24m: 31
Adoption not part of the score
1262 stars · 94 forks observed · 2026-09-03
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
application · maturity active
etl data-science workflow-automation scheduling rag mcp data-visualization developer-tools data-science analytics databases self-hosted windows self-hosted cross-platform 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
9 sources
- readme: https://github.com/slothflowlabs/duckle · fetched 2026-09-03 · db2281238d68
- homepage: https://duckle.org/ · fetched 2026-08-29 · 09f4ed1e1fe7
- site_page: https://duckle.org/docs/components.html · fetched 2026-08-29 · 7de688f4d33b
- site_page: https://duckle.org/docs/automation.html · fetched 2026-08-29 · e05658e46f8d
- site_page: https://duckle.org/docs/index.html · fetched 2026-08-29 · d96a0848a95a
- site_page: https://duckle.org/docs/learn.html · fetched 2026-08-29 · f849e575e179
- site_page: https://duckle.org/docs/integrations.html · fetched 2026-08-29 · 0555d3253a7c
- site_page: https://duckle.org/docs/ai-duckie.html · fetched 2026-08-29 · 6682df30fb2d
- site_page: https://duckle.org/docs/getting-started.html · fetched 2026-08-29 · 7da3c07e3ad7
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| slothflowlabs/duckle | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="slothflowlabs/duckle")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem