# sfu-db/connector-x

Fastest library to load data from DB to DataFrames in Rust and Python

Repository: https://github.com/sfu-db/connector-x
Canonical: https://ross.abutalabs.com/products/connector-x
Homepage: https://sfu-db.github.io/connector-x
Language: Rust
License: MIT
License Family: permissive
Topics: rust, python, database, sql, dataframe, cpp
Last push: 2026-08-17T14:23:21+00:00

## Health v2 (maintenance only)
Score: 83/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 54, longevity 100
- inputs: {"age_days": 2058, "days_push": 16, "days_rel": 228, "gap_med": 80, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2646, forks 221 (observed 2026-08-28T04:07:06.746645+00:00)

## What it is
ConnectorX is a Rust-based library with Python bindings that loads data from databases into DataFrames (pandas, Arrow, Polars) as fast and memory-efficiently as possible. It supports parallel partitioned loading and experimental federated queries across multiple databases with a single read_sql call.

## Use cases
- load a large postgres table into a pandas dataframe fast
- export sql query results to arrow or parquet
- parallelize database reads by partitioning on a numeric column
- join tables from two different databases in one query
- replace pd.read_sql for better performance and memory usage
- bulk extract data from a database for etl pipelines

## When to choose
- you need the fastest possible database-to-DataFrame loading in Python
- you are loading multi-GB tables and memory efficiency matters
- you want parallel reads from a single database via partitioning
- you need to combine data from multiple databases in one query

## When to avoid
- you need writes or general ORM functionality - it is read-only
- your queries are small and simple where driver overhead is negligible
- you need partitioning on non-numeric or nullable columns
- you need a pure-Python dependency-free solution

## Facets
- artifact type: library
- maturity: active
- function: database-driver, etl, data-science
- domain: databases, data-science, analytics
- platform: python, rust, cross-platform
- tags: dataframe, sql, parallel-loading, pandas, arrow, federated-queries, data-engineering

## Member repositories
- sfu-db/connector-x (main) score 83

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:06.746645+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 2026-08-30T02:18:58.737682+00:00, confidence not recorded.
  - readme: https://github.com/sfu-db/connector-x (fetched 2026-08-28T04:07:06.746645+00:00, sha d23c723ae5af)
  - homepage: https://sfu-db.github.io/connector-x (fetched 2026-08-29T10:01:47.352404+00:00, sha e737e762e514)
- Data as of 2026-08-30T08:39:29.467469+00:00.