Markets · bedrock market · provisional

Official R Client Packages on CRAN

Distribution market (official r client libraries on cran; providers ranked). The Kin Score Market layer reads each provider in its market: who it integrates with, how deep those integrations go, and where the market publishes its own structure. Methodology.

11providers measured
5 (45.5%)declare their own
0 (0.0%)covered by others only
6 (54.5%)distribution only (sell through, not integrations)
0 (0.0%)undeclared
3declare compatibility (report only, not weighted)
0in-market workflows shown
Provisional. Provisional and unweighted: the Market layer is not part of the composite or agent readiness. Leader lists are read within a position, never as one ranking. A provider that declares nothing we can read is shown as undeclared, with no number: we never infer integrations.

Where this market publishes its structure

Own = declares at least one integration itself; covered = visible only because an aggregator, standards body, regulator or partner contract names it; distribution-only = listed only on cloud marketplaces it sells through, a channel reported beside, never counted as its own declared integrations; undeclared = nothing we can read, so no number; declares_compatibility = providers with a `compatible` shape vote, report only (kin, 2026-10-13): never counted as own, never in depth or position.

Taxonomy how this market maps onto apis.io

Derived 2026-10-23 from the 11 providers in this market we could resolve in the catalog. The percentage is the share of those providers carrying each one; it describes the market, not the tag or industry. Tag groups have no page of their own yet, so they are listed unlinked.

TagsAnalytics 27%, Data Science 27%
Tag groupsAnalytics 27%, Python 27%
IndustriesData & Analytics 73%, Artificial Intelligence 45%
AreasMachine Learning 36%
CapabilitiesCybersecurity Management 27%

share of resolved cohort carrying it; tags >=0.20 & >=3 members (max 12, junk dropped), tag_groups >=0.20 (cooccurrence, non-cross-cutting; max 8), industries >=0.20 (max 6), areas >=0.10 (max 6; areas are keyword-matched and sparse), capabilities L1 >=0.20 (max 8); derive-market-taxonomy.py

Leaders by position (provisional)

Provisional: grouped by position, depth compared within a position only. Distribution (cloud marketplaces) and iPaaS bridges are counted beside position, never inside it. Unknown-builder listings are left out of position shares and counted here.

builds-on 2 · publishes apps on other platforms' stores

ProviderDepthIntegrationsIn / outUnknown builderDistributioniPaaS bridgeMix
Posit 45.2 7 0 / 7 0 3 0 standard 12%, builds-on-platform 50%, distribution 38%
Treasure Data 34.5 4 0 / 4 0 3 0 builds-on-platform 25%, distribution 75%

standard 1 · listed by a voluntary standard's own directory

ProviderDepthIntegrationsIn / outUnknown builderDistributioniPaaS bridgeMix
SAS Institute 55.8 13 0 / 13 0 7 0 contract 12%, standard 31%, builds-on-platform 12%, distribution 44%

mixed 1 · no single mode dominates

ProviderDepthIntegrationsIn / outUnknown builderDistributioniPaaS bridgeMix
EODHD 42.2 3 0 / 3 0 1 0 coverage 33%, builds-on-platform 33%, distribution 33%

long-tail 1 · reached only through iPaaS bridges

ProviderDepthIntegrationsIn / outUnknown builderDistributioniPaaS bridgeMix
OpenAQ 12.1 thin 2 0 / 2 0 1 1 ipaas-bridge 50%, distribution 50%

distribution 6 · only sells through cloud marketplaces

ProviderDepthIntegrationsIn / outUnknown builderDistributioniPaaS bridgeMix
NameGender 28.8 3 0 / 3 0 3 0 distribution 100%
Nixtla 28.8 3 0 / 3 0 3 0 distribution 100%
OddsRelay 28.8 3 0 / 3 0 3 0 distribution 100%
SolveBio 28.7 4 0 / 4 0 4 0 distribution 100%
openEO 19.2 thin 2 0 / 2 0 2 0 distribution 100%
Domino Data Lab 9.6 thin 1 0 / 1 0 1 0 distribution 100%

Generated 2026-10-24 from API Evangelist's own files; nothing on this page is a model's judgement. Provisional and unweighted; not part of the Kin Score composite or agent readiness. Read the Market layer methodology. Disagree with an edge? Every edge cites its evidence and can be corrected through the normal correction path.