GoldenMatch

vgoldenmatch-duckdb-v0.6.0 scope: goldenmatch-duckdb Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 1mo Data Pipelines & ETL

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

Topics

data-cleaning data-engineering data-matching data-quality deduplication entity-resolution

+14 more

fellegi-sunter fuzzy-matching knowledge-graph llm master-data-management mcp-server polars pprl python record-linkage rust splink typescript zero-config

Summary

AI summary

Native-direct SQL graph UDFs and local embedding kernel improve performance without JSON/CPython bridges.

Changes in this release

Type	Severity	Summary	CVE
Feature	Medium	goldenmatch_connected_components and related UDFs now run native-direct via pyo3-free graph-core with Arrow I/O. goldenmatch_connected_components and related UDFs now run native-direct via pyo3-free graph-core with Arrow I/O. Source: llm_adapter@2026-06-05 Confidence: high	—
Feature	Medium	goldenmatch_embed_local runs goldenembed-rs ONNX kernel via goldenmatch-embed wheel; no network or torch required. goldenmatch_embed_local runs goldenembed-rs ONNX kernel via goldenmatch-embed wheel; no network or torch required. Source: llm_adapter@2026-06-05 Confidence: high	—
Dependency	Low	Embed extra pulls goldenmatch-embed 0.1.0 via pip install goldenmatch-duckdb[embed]. Embed extra pulls goldenmatch-embed 0.1.0 via pip install goldenmatch-duckdb[embed]. Source: llm_adapter@2026-06-05 Confidence: high	—

Full changelog

Native-direct SQL graph UDFs + embedding (#509).

goldenmatch_connected_components / goldenmatch_pair_dedup (+ _str variants) now run native-direct over the pyo3-free graph-core kernel (no JSON/CPython bridge), with Arrow columnar I/O and accept-both int64/string ids.
goldenmatch_embed_local runs the goldenembed-rs ONNX kernel via the new goldenmatch-embed wheel (pip install goldenmatch-duckdb[embed]); no network, no torch.

Requires goldenmatch-duckdb's usual deps; the embed extra pulls goldenmatch-embed 0.1.0.

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Earlier breaking changes

v3.1.0 `GOLDENMATCH_FRAME=polars` now requires the `[polars]` extra; raises error without it.
vgoldencheck-v3.0.0 `inferred_type` emits neutral dtype vocabulary (str/int/uint/float/date/datetime/bool/other) instead of raw Polars dtypes.
vgoldencheck-v3.0.0 'inferred_type' now emits a neutral dtype vocabulary instead of raw Polars dtype strings.
vgoldencheck-v3.0.0 `scan_file`, `scan_dataframe`, and CLI `check` now run without Polars, using Arrow-native pyarrow.Table.
v3.0.0 Result frames now return pyarrow.Table instead of Polars DataFrame.