Public record
Software health reportschema 0.27.0 · metrics 2.10.0 · 2026-07-31 05:16 UTC

duckdb / dbt-duckdb

dbt adapter for DuckDB

PythonApache-2.0★ 1,325 stars⑂ 137 forkssince Sep 2020View on GitHub ↗

duckdb/dbt-duckdb holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Vitality (86/100) and lowest on Security (40/100). It was last updated 3 days ago. A single contributor accounts for most of its recent work.

81
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

81
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

DuckDB FoundationOrganization
1,650 followers92 public repossince Apr 2021

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdbt-duckdbpoints to another repo — not scored1.10.1-48163 days agosetupdistutils

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

86Excellent · 21% of overall
How it's scored
36/36Push recencylast push 3 days ago
26.3/36Commit cadence38/52 weeks with commits
18/18Commit volume121 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year121
human_commit_share0.56
days_since_last_push3
active_weeks_last_year38
How it's scored
27/27Ships releases31 releases published
27/36Release recencylatest release 163 days ago
19.8/27Release cadencea release every ~56.5 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count31
latest_release_tag1.10.1
releases_from_tagsno
days_since_latest_release163
mean_days_between_releases56.5

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

73Good · 17% of overall
How it's scored
50.6/60Stars1,325 stars
17.8/25Forks137 forks
7.5/15Watchers23 watchers
Inputs used
forks137
stars1,325
watchers23
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

66Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
5.9/22.5Commit distributiontop contributor authored 74% of commits
13.5/13.5Contributor breadth54 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor1
contributors_sampled54
top_contributor_share0.739
How it's scored
29.7/42Issue resolution71% of issues closed
25.6/30PR acceptance450/527 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs450
open_issues71
closed_issues171
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.707
closed_unmerged_prs77
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
23.1/25Owner reach1,650 followers of duckdb
23.6/25Track record92 public repos, account ~5 yr old
Inputs used
followers1,650
owner_typeOrganization
is_verified
owner_loginduckdb
public_repos92
account_age_days1,941
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

75Good · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
16/16Linter config.flake8, tox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics2 topics
0/10Wiki
Inputs used
topicsdbt, duckdb
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

40Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestssetup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages57
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:dbt-duckdb@1.10.1 runtime dependency closure — what installing the published package pulls in — 57 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

61Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history55 of 56 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.982
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config.flake8, tox.ini
11/11Static type checkingmypy.ini
0/10Reproducible environment
10/10Demonstrated agent practice15 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance44 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini
agent_commit_share0.15
toolchain_manifests
dependency_bot_commit_share0.44
How it's scored
27/45Type-checkable codePython with type-check config (mypy.ini)
55/55Manageable file sizes0/96 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes27,188
source_files_sampled96
oversized_source_files0

Key facts

1,325GitHub stars
54contributors
121commits, last 12 months
3days since last push
31releases
1bus factor
71open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'dbt-duckdb' points at a different repository (https://github.com/jwills/dbt-duckdb); excluded from ecosystem scoring
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 137 ⇿
0Stars
137Forks
31Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

025507510012515013032021-102024-032026-07
Major 0Minor 7Patch 24

Each point covers 5 days.

Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIdbt-common>=1,<2setup.cfg
PyPIdbt-adapters>=1,<2setup.cfg
PyPIduckdb>=1.0.0setup.cfg
PyPIdbt-core>=1.8.0setup.cfg
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Dependency advisories 0

Installing pypi:dbt-duckdb@1.10.1 pulls in 57 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.27.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.