Data Engineering
Data EngineeringDataEngineeringdata-engineering
Providers using this tag (47)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Strong 5 Solid coverage with minor gaps
Developing 13 Usable, with meaningful gaps to close
Thin 12 Limited public surface area
Emerging 12 Early or largely undocumented
Minimal 5 Almost no public developer surface
APIs with this tag (4)
Ranked by the provider's API Evangelist rating — the Kin Score is scored per provider, not per API, so every API of a provider shares its band. How the rating works →
Strong 2 Solid coverage with minor gaps
Thin 1 Limited public surface area
Emerging 1 Early or largely undocumented
Score breakdown
Related tags
Where this tag comes from
Cohort brief
Auto-generatedThe 47 providers in the APIs.io catalog tagged Data Engineering, scored on the Kin Score. Every figure below is computed from the catalog — nothing here is written.
| Facet | This cohort | Catalog | Difference | Scored |
|---|---|---|---|---|
| Developer Ergonomics | 40.8 | 17.9 | +22.9 | 47 |
| Access Clarity | 36.4 | 22.3 | +14.1 | 47 |
| Operational Transparency | 21.4 | 11.3 | +10.1 | 47 |
| Contract Quality | 26.8 | 17.5 | +9.3 | 47 |
| Contract Governance | 14.5 | 6.4 | +8.1 | 47 |
| Discoverability | 64.6 | 60.4 | +4.2 | 47 |
A facet is averaged over the members that carry it, not over the whole cohort — the “Scored” column is that count. Averaging an absent facet as zero would score our own coverage gaps as the providers’ posture.
| Artifact | This cohort | Catalog | Difference |
|---|---|---|---|
| MCP server (any) | 32% | 16% | +16 |
| MCP server (first-party) | 21% | 7% | +14 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 15% | 9% | +6 |
| Security | 98% | 88% | +10 |
| Arazzo workflows | 9% | 2% | +7 |
| Governance rules | 28% | 13% | +15 |
mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
- 1 Dagster 62.1
- 2 Databricks 59.1
- 3 Azure Databricks 56.5
- 4 Tower 55.8
- 5 Snowflake 54.6
- 6 Astronomer 53.1
- 7 TetraScience 52.9
- 8 API Calendrier Marocain | Jours Fériés & Ouvrables REST + SDK Python 50.5
- 9 Artie 50.2
- 10 Flume Health 49.7
- 1 Tower 41.6
- 2 Databricks 40.1
- 3 Snowflake 35.8
- 4 Apache Airflow 29.8
- 5 Alteryx 28.4
- 6 Altimate AI 28.2
- 7 Artie 27.1
- 8 Flume Health 26.9
- 9 API Calendrier Marocain | Jours Fériés & Ouvrables REST + SDK Python 26.8
- 10 Azure Databricks 26.5
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.
MCP server
One button, every client — Claude, Cursor, VS Code and the rest.
https://apis.io/mcp
Tools for tags
7 MCP tools reach this
find_tagsBrowse and filter every tag in the catalog.get_cohortThis tag as a scored cohort — every provider carrying it, with scores.cohort_statsPRO — the distribution across this tag: mean, median, band split, adoption rates.cohort_rankingsPRO — the leaderboard, on composite AND agent-readiness axes.apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.resolveTurn a domain, URL or GitHub org into the provider it belongs to.find_cohortsEvery scored population of providers in the catalog.
Call it yourself
curl for this page
curl "https://apis.io/api/v1/tags/data-engineering"curl "https://apis.io/api/v1/tags?limit=25"curl "https://apis.io/api/v1/cohorts/tag/data-engineering"curl "https://apis.io/api/v1/cohorts/tag/data-engineering/stats" \
-H "X-API-Key: $APIS_IO_KEY"Discovery needs no key. Ratings and market analysis are Pro.