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.

Databand is profiled on the APIs.io network. Tagged areas include Company, Enterprise, Data Observability, Data Engineering, and Data Pipeline.

Databand’s developer surface includes documentation, getting-started guide, support, CLI, changelog, and 13 more developer resources.

🌐 Visit website 📡 Source on GitHub

18.0/100 emerging ▬ flat Agent 0/100 human only self hosted · Apache-2.0 Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Enterprise Data Observability Data Engineering Data Pipeline Data Quality DataOps Machine-Learning Open-Source SDK CLI IBM

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 18.0/100 · emerging

Contract Quality 0.0 / 23

Developer Ergonomics 8.1 / 18

Access Clarity 0.0 / 18

Operational Transparency 2.2 / 12

Contract Governance 0.0 / 11

Discoverability 5.2 / 9

Open Source Surface 2.5 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 90 points between them, because the conditional facet above carries the other 10. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 90% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/databand: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Databand Domain Security

DMARC

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

DeveloperPortal

DeveloperPortal

Documentation 2

Reference material describing how the API behaves

ContributionGuide

ContributionGuide

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Build 5

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

SourceCode

Packages

SDKs

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Support

Support

ChangeLog

ChangeLog

Commercial 1

Pricing, plans, and the legal terms of use

License

License

Company 2

The organization behind the API

Website

Website

Homepage

Homepage

Other 1

Properties that don't map to a standard resource type

ParentCompany

ParentCompany

Source (apis.yml)

aid: databand
name: Databand
description: 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.
url: https://raw.githubusercontent.com/api-evangelist/databand/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- accel
- bessemer-venture-partners
x-tier: stub
x-tier-reason: portfolio-lead
x-acquired-by: IBM (2022)
deliveryModel:
  model: self-hosted
  license: Apache-2.0
  open_source: true
  commercial: false
  callable_host: false
  label: Self-hosted open source · you run it yourself
  confidence: high
  source:
  - license
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://avatars.githubusercontent.com/u/48434944
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Enterprise
- Data Observability
- Data Engineering
- Data Pipeline
- Data Quality
- DataOps
- Machine-Learning
- Open-Source
- SDK
- CLI
- IBM
tags_raw:
- Company
- Enterprise
- Data Observability
- Data Engineering
- Data Pipelines
- Data Quality
- DataOps
- Machine Learning
- Open Source
- SDK
- CLI
- IBM
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: ParentCompany
  url: https://apis.io/providers/ibm/
  name: IBM
  x-relationship: acquired
  x-evidence: 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.
- type: IssueTracker
  url: https://github.com/databand-ai/dbnd/issues
- type: ContributionGuide
  url: https://github.com/databand-ai/dbnd/blob/develop/CONTRIBUTING.md
- type: License
  name: Apache-2.0
  url: https://github.com/databand-ai/dbnd/blob/develop/LICENSE
- type: Website
  url: https://databand.ai/
- type: Homepage
  url: https://www.ibm.com/products/watsonx-data-integration/data-observability
- type: Documentation
  url: https://www.ibm.com/docs/en/dobd
- type: GettingStarted
  url: https://www.ibm.com/docs/en/dobd
- type: DeveloperPortal
  url: https://dbnd.readme.io/
- type: GitHubOrganization
  url: https://github.com/databand-ai
- type: SourceCode
  url: https://github.com/databand-ai/dbnd
- type: Support
  url: mailto:contact@databand.ai
- type: Packages
  url: packages/databand-packages.yml
- type: SDKs
  url: packages/databand-packages.yml
- type: CLI
  url: cli/databand-cli.yml
- type: ChangeLog
  url: changelog/databand-changelog.yml
- type: DomainSecurity
  url: security/databand-domain-security.yml
- type: LLMsTxt
  url: llms/databand-llms.txt
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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