# deepseek-ai/smallpond

A lightweight data processing framework built on DuckDB and 3FS.

Repository: https://github.com/deepseek-ai/smallpond
Canonical: https://ross.abutalabs.com/products/smallpond
Language: Python
License: MIT
License Family: permissive
Topics: data-processing, duckdb
Last push: 2025-03-05T18:23:54+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 9, release rhythm 35, longevity 39
- inputs: {"age_days": 555, "days_push": 546, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5000, forks 455 (observed 2026-08-28T04:09:04.481381+00:00)

## What it is
Smallpond is a lightweight distributed data processing framework built on DuckDB and DeepSeek's 3FS shared file system. It lets users process petabyte-scale datasets with SQL and dataframe-style operations without running long-lived services.

## Use cases
- process large parquet datasets with SQL
- sort terabytes of data across a cluster
- run distributed group-by aggregations on parquet files
- batch ETL over a shared filesystem
- repartition and transform big datasets in Python

## When to choose
- you need DuckDB-style SQL processing scaled to many nodes
- you have a shared filesystem like 3FS and want no long-running services
- you want lightweight batch processing of parquet data at PB scale

## When to avoid
- you need streaming or real-time processing
- you want a full Spark/Flink ecosystem with rich connectors
- you only process small datasets that fit on one machine

## Facets
- artifact type: framework
- maturity: active
- function: etl, data-science, database, streaming
- domain: big-data, data-science
- platform: python
- tags: duckdb, distributed-data-processing, parquet, sql, 3fs, dataframe, data-engineering, linux, docker

## Member repositories
- deepseek-ai/smallpond (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:04.481381+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 2026-08-29T18:17:35.630232+00:00, confidence not recorded.
  - readme: https://github.com/deepseek-ai/smallpond (fetched 2026-08-28T04:09:04.481381+00:00, sha 8ad6562a5fec)
  - registry_pypi: https://pypi.org/pypi/smallpond/json (fetched 2026-08-29T08:58:30.049877+00:00, sha a0658b59a795)
- Data as of 2026-08-30T08:39:29.467469+00:00.