Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 19:55 UTC

databricks / dbt-databricks

A dbt adapter for Databricks.

PythonApache-2.0★ 382 stars⑂ 225 forkssince Oct 2021View on GitHub ↗

KindLibraryCommand-line toolhow this is determined

databricks/dbt-databricks holds a health index of 97 out of 100, placing it in the Exceptional band. It scores highest on Vitality (96/100) and lowest on Security (63/100). It was last updated today. 3 contributors account for most of its recent work.

overall / 100

Exceptional

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.

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)

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 85 is calibrated to 97 on the published index scale (record calibration 2026-08-02).

Ownership

DatabricksOrganization · verified domain

4,171 followers251 public repossince Jul 2013

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	dbt-databricks	1.12.7	3,741,376	187	7 days ago

Metrics by category

Vitality

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

96Exceptional · 21% of overall

Development activity

94Exceptional

How it's scored

36/36	Push recency — last push 0 days ago
30.5/36	Commit cadence — 44/52 weeks with commits
18/18	Commit volume — 247 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	247
human_commit_share	1
days_since_last_push	0
active_weeks_last_year	44

Release discipline

100Exceptional

How it's scored

27/27	Ships releases — 100 releases published
36/36	Release recency — latest release 7 days ago
27/27	Release cadence — a release every ~19.5 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	100
latest_release_tag	v1.12.7
releases_from_tags	no
days_since_latest_release	7
mean_days_between_releases	19.5

Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

80Excellent · 17% of overall

Popularity & adoption

69Good

How it's scored

41.9/60	Stars — 382 stars
19.6/25	Forks — 225 forks
7.2/15	Watchers — 21 watchers

Inputs used

forks	225
stars	382
watchers	21
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	2
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	github.com
has_pull_request_template	yes

Ecosystem adoption (downloads)

100Exceptional

How it's scored

80/80	Monthly downloads — 3,741,376 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	dbt-databricks
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	3,741,376
unverified_packages_excluded	—

Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

87Excellent · 23% of overall

Maintainer resilience (bus factor)

75Good

How it's scored

36/54	Bus factor — 3 contributor(s) cover half of all commits
15.4/22.5	Commit distribution — top contributor authored 32% of commits
13.5/13.5	Contributor breadth — 100 contributors
10/10	OpenSSF Scorecard: Contributors — project has 12 contributing companies or organizations

Inputs used

bus_factor	3
contributors_sampled	100
top_contributor_share	0.317

Issue & PR responsiveness

79Good

How it's scored

35.2/42	Issue resolution — 84% of issues closed
25.5/30	PR acceptance — 923/1,087 decided PRs merged
5.2/13	Newcomer PR acceptance — 2/5 first-time contributors' PRs merged in 30d
13.5/15	OpenSSF Scorecard: Code-Review — Found 28/30 approved changesets -- score normalized to 9

Inputs used

merged_prs	923
open_issues	94
closed_issues	485
prs_merged_7d	3
prs_decided_7d	6
prs_merged_30d	25
prs_decided_30d	32
issue_closed_ratio	0.838
closed_unmerged_prs	164
first_time_authors_30d	4
first_time_prs_merged_30d	2
first_time_prs_decided_30d	5

Ownership & stewardship

100Exceptional

How it's scored

30/30	Ownership backing — organization-owned
20/20	Verified domain
25/25	Owner reach — 4,171 followers of databricks
25/25	Track record — 251 public repos, account ~13 yr old

Inputs used

followers	4,171
owner_type	Organization
is_verified	yes
owner_login	databricks
public_repos	251
account_age_days	4,847

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 7 days ago
20/20	Version history — 187 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	dbt-databricks
ecosystems	pypi
any_deprecated	no
min_days_since_publish	7

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall

Engineering practices

92Excellent

How it's scored

24/24	CI workflows — 14 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
18/20	OpenSSF Scorecard: CI-Tests — 28 out of 30 merged PRs checked by a CI test -- score normalized to 9

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://databricks.com
10/10	Repository description
10/10	Topics — 4 topics
10/10	Wiki

Inputs used

topics	dbt, sql, etl, databricks
has_wiki	yes
homepage	https://databricks.com
docs_site	https://databricks.com
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

63Moderate · 16% of overall

Security posture

57Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0.8/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5	CI-Tests — 28 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6.8/7.5	Code-Review — Found 28/30 approved changesets -- score normalized to 9
2.5/2.5	Contributors — project has 12 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
5/5	Pinned-Dependencies — all dependencies are pinned
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 49 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	5.6

Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

86Excellent

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
11.4/25	Indirect dependencies free of known advisories — 1 affected: oauthlib 3.3.1 (moderate 6.8)
40/40	No advisories left outstanding — no advisory has been public longer than 90 days

Inputs used

source	osv
advisories	4
affected_packages	1
assessed_packages	77
unassessed_packages	0
affected_by_severity	moderate 1
direct_affected_packages	0

Matched the pypi:dbt-databricks@1.12.7 runtime dependency closure — what installing the published package pulls in — 77 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.

73Good · 4% of overall

Agent context & guidance

100Exceptional

How it's scored

45/45	Agent instructions — AGENTS.md, CLAUDE.md
15/15	Machine-readable docs (llms.txt) — llms.txt served by the project website (https://databricks.com/llms.txt)
40/40	Legible commit history — 100 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	yes
llms_txt_url	https://databricks.com/llms.txt
legible_history_share	1
agent_instruction_files	AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	25,278

Verify loop (build / test / typecheck)

60Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
0/11	Static type checking
10/10	Reproducible environment — lockfile
2/10	Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
5/8	Automated maintenance — dependency automation configured, none observed in the sampled commits
10/10	OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.01
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

54Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.5/55	Manageable file sizes — 3/331 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	93,552
source_files_sampled	331
oversized_source_files	3

Key facts

382GitHub stars

100contributors

247commits, last 12 months

0days since last push

100releases

3bus factor

94open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 225 ⇿

0Stars

225Forks

100Releases

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.

Major 0Minor 8Patch 80

Each point covers 5 days.

OpenSSF Scorecard 5.6 / 10

5.6aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-10-19 19:54 UTC

10	Binary-Artifacts	no binaries found in the repo
1	Branch-Protection	branch protection is not maximal on development and all release branches
9	CI-Tests	28 out of 30 merged PRs checked by a CI test -- score normalized to 9
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
9	Code-Review	Found 28/30 approved changesets -- score normalized to 9
10	Contributors	project has 12 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
10	Pinned-Dependencies	all dependencies are pinned
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	49 existing vulnerabilities detected

Direct dependencies 9

Registry	Package	Version constraint	Manifest
PyPI	click	`>=8.2.0, <9.0.0`	pyproject.toml
PyPI	databricks-sdk	`>=0.68.0, <0.118.0`	pyproject.toml
PyPI	databricks-sql-connector	`>=4.1.1, <4.4.1`	pyproject.toml
PyPI	dbt-adapters	`>=1.22.0, <1.25.0`	pyproject.toml
PyPI	dbt-common	`>=1.37.0, <1.39.0`	pyproject.toml
PyPI	dbt-core	`>=1.11.2, <1.12.6`	pyproject.toml
PyPI	dbt-spark	`>=1.10.0, <1.11.0`	pyproject.toml
PyPI	packaging	`>=21.0, <26.0`	pyproject.toml
PyPI	pydantic	`>=1.10.0, <2.13.0`	pyproject.toml

All dependencies 140

Full resolved dependency set from the GitHub dependency graph: 18 direct and 122 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	click	`8.2.0`	direct
PyPI	click	`8.3.1`	direct
PyPI	databricks-sdk	`0.117.0`	direct
PyPI	databricks-sdk	`0.68.0`	direct
PyPI	databricks-sql-connector	`4.1.2`	direct
PyPI	databricks-sql-connector	`4.4.0`	direct
PyPI	dbt-adapters	`1.22.0`	direct
PyPI	dbt-adapters	`1.24.5`	direct
PyPI	dbt-common	`1.37.2`	direct
PyPI	dbt-common	`1.38.0`	direct
PyPI	dbt-core	`1.11.2`	direct
PyPI	dbt-core	`1.12.5`	direct
PyPI	dbt-spark	`1.10.0`	direct
PyPI	dbt-spark	`1.10.1`	direct
PyPI	packaging	`21.0`	direct
PyPI	packaging	`25.0`	direct
PyPI	pydantic	`1.10.0`	direct
PyPI	pydantic	`2.12.5`	direct
PyPI	agate	`1.9.1`	indirect
PyPI	annotated-types	`0.7.0`	indirect
PyPI	attrs	`26.1.0`	indirect
PyPI	babel	`2.18.0`	indirect
PyPI	certifi	`2026.2.25`	indirect
PyPI	certifi	`2026.4.22`	indirect
PyPI	cffi	`2.0.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	charset-normalizer	`3.4.6`	indirect
PyPI	charset-normalizer	`3.4.7`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`7.14.0`	indirect
PyPI	cryptography	`46.0.5`	indirect
PyPI	cryptography	`48.0.0`	indirect
PyPI	daff	`1.4.2`	indirect
PyPI	dbt-core-experimental-parser	`2.0.0b2`	indirect
PyPI	dbt-extractor	`0.6.0`	indirect
PyPI	dbt-protos	`1.0.498`	indirect
PyPI	dbt-protos	`1.0.541`	indirect
PyPI	dbt-semantic-interfaces	`0.9.0`	indirect
PyPI	dbt-tests-adapter	`1.20.0`	indirect
PyPI	debugpy	`1.8.20`	indirect
PyPI	deepdiff	`8.6.2`	indirect
PyPI	distlib	`0.4.0`	indirect
PyPI	et-xmlfile	`2.0.0`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	execnet	`2.1.2`	indirect
PyPI	filelock	`3.29.0`	indirect
PyPI	freezegun	`1.5.1`	indirect
PyPI	freezegun	`1.5.5`	indirect
PyPI	google-auth	`2.49.1`	indirect
PyPI	google-auth	`2.52.0`	indirect
PyPI	identify	`2.6.19`	indirect
PyPI	idna	`3.11`	indirect
PyPI	idna	`3.15`	indirect
PyPI	importlib-metadata	`8.8.0`	indirect
PyPI	importlib-metadata	`8.9.0`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	isodate	`0.7.2`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	leather	`0.4.1`	indirect
PyPI	librt	`0.11.0`	indirect
PyPI	lz4	`4.4.5`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	mashumaro	`3.14`	indirect
PyPI	metricflow	`0.213.0`	indirect
PyPI	more-itertools	`10.8.0`	indirect
PyPI	msgpack	`1.1.2`	indirect
PyPI	mypy	`1.19.1`	indirect
PyPI	mypy-extensions	`1.1.0`	indirect
PyPI	networkx	`3.4.2`	indirect
PyPI	networkx	`3.6.1`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	numpy	`2.2.6`	indirect
PyPI	numpy	`2.4.3`	indirect
PyPI	oauthlib	`3.3.1`	indirect
PyPI	openpyxl	`3.1.5`	indirect
PyPI	opentelemetry-api	`1.44.0`	indirect
PyPI	orderly-set	`5.5.0`	indirect
PyPI	pandas	`2.2.3`	indirect
PyPI	parsedatetime	`2.6`	indirect
PyPI	pathspec	`0.12.1`	indirect
PyPI	platformdirs	`4.9.6`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	pre-commit	`4.6.0`	indirect
PyPI	protobuf	`6.33.6`	indirect
PyPI	pyarrow	`23.0.1`	indirect
PyPI	pyarrow	`24.0.0`	indirect
PyPI	pyasn1	`0.6.3`	indirect
PyPI	pyasn1-modules	`0.4.2`	indirect
PyPI	pybreaker	`1.4.1`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydantic-core	`2.41.5`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pyjwt	`2.12.1`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pytest	`8.3.5`	indirect
PyPI	pytest	`9.0.3`	indirect
PyPI	pytest-cov	`6.0.0`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	pytest-dotenv	`0.5.2`	indirect
PyPI	pytest-rerunfailures	`16.2`	indirect
PyPI	pytest-timeout	`2.4.0`	indirect
PyPI	pytest-xdist	`3.6.1`	indirect
PyPI	pytest-xdist	`3.8.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-discovery	`1.3.1`	indirect
PyPI	python-dotenv	`1.2.2`	indirect
PyPI	python-slugify	`8.0.4`	indirect
PyPI	pytimeparse	`1.1.8`	indirect
PyPI	pytz	`2026.1.post1`	indirect
PyPI	pytz	`2026.2`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	rapidfuzz	`3.14.5`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	requests	`2.32.5`	indirect
PyPI	requests	`2.34.2`	indirect
PyPI	rpds-py	`0.30.0`	indirect
PyPI	ruff	`0.14.2`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	snowplow-tracker	`1.1.0`	indirect
PyPI	sqlglot	`30.12.0`	indirect
PyPI	sqlparams	`6.2.0`	indirect
PyPI	sqlparse	`0.5.4`	indirect
PyPI	sqlparse	`0.5.5`	indirect
PyPI	tabulate	`0.10.0`	indirect
PyPI	text-unidecode	`1.3`	indirect
PyPI	thrift	`0.20.0`	indirect
PyPI	thrift	`0.24.0`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	types-requests	`2.33.0.20260513`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	typing-inspection	`0.4.2`	indirect
PyPI	tzdata	`2025.3`	indirect
PyPI	tzdata	`2026.2`	indirect
PyPI	urllib3	`2.6.3`	indirect
PyPI	urllib3	`2.7.0`	indirect
PyPI	virtualenv	`21.3.3`	indirect
PyPI	zipp	`3.23.0`	indirect
PyPI	zipp	`3.23.1`	indirect

Dependency advisories 1

Installing pypi:dbt-databricks@1.12.7 pulls in 77 packages, direct and transitive: 1 carry known advisories, of which 0 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
oauthlib	`3.3.1`	indirect	moderate	4	`4.0.0`

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.

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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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