Databand
DBND (Databand) is an open-source Python framework — a library, a set of APIs, and a CLI — for building, tracking, and observing data pipelines across data ingestion, preparation, ETL/ELT, and machine-learning workflows. It collects pipeline metadata (runs, metrics, dataframes, schemas) to give data-engineering teams a system of record for runs and to detect pipeline failures and data quality issues before they hit downstream consumers. The DBND SDK integrates with Apache Airflow, Apache Spark, Databricks, dbt, and IBM DataStage. Databand was acquired by IBM in 2022 and is now IBM Databand, part of IBM's data observability offering; the open-source DBND SDK remains published on PyPI and GitHub under the databand-ai organization.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Databand the way a machine reads it — 1 machine-readable artifact, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Databand scores 18.6/100 (emerging), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Databand
Each block below is one kind of artifact we hold for Databand. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Databand — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 2
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 5
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Company 2
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/databand · machine-readable index on apis.io