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Data Marketplace · Markets & technology

GitHub Repositories Dataset

Map public GitHub repositories, organizations, releases, languages, topics, and activity for software ecosystem research.

Request GitHub sampleView fields
  • Records Repository · Organization · Release
  • Source GitHub
  • Formats JSON · CSV · Parquet
Dataset preview · github repositoriesReady
Observation 01

An illustrative view of how repository, organization, rel…

.

Field 01
An illustrative view of how repository, organization, rel…
{
  "repository": "example-org/example-project",
  "repository_url": "https://example.test/repository",
  "description": "Illustrative repository record",
  "languages": [
    "JavaScript",
    "Python"
  ],
  "topics": [
    "data"
  ],
  "latest_release": {
    "tag": "v2.4.0"…
An illustrative view of how repository, organization, release and collection context arrive together.

Schema and fields

Build on GitHub records with context attached.

Start with repository, organization, release. Source identity, collection time, and field meaning stay connected so records can move into analysis without losing their context.

repository string

Owner and repository identity

repository_url url

Public source URL

description string

Public repository summary

languages array

Observed language context

topics array

Public repository topics

latest_release object

Available public release context

activity object

Observed public activity signals

captured_at timestamp

Collection time

Freshness and delivery

Keep GitHub data aligned with your analysis cycle.

Use a dated ecosystem snapshot or recurring refreshes when repositories, releases, languages, and public activity need to be compared over time.

Snapshot Start from a dated baseline Selected scope and collection window

Refresh Receive recurring updates Cadence and change behavior

Format Use JSON, CSV, or Parquet Schema, partitioning, and manifest

Validation Run repeatable checks Counts, fields, missing states, and version

GitHub applications

Put GitHub records to work.

Use source-linked, time-stamped records for technology ecosystem mapping, plus open-source project research. Each application starts from the same documented fields and collection context.

01

Technology ecosystem mapping

Compare public repositories, organizations, topics, languages, and release patterns.

02

Open-source project research

Build source-linked project records for selected technologies, organizations, or categories.

03

Release and activity monitoring

Track newly observed releases and public repository activity across a controlled scope.

From sample to production

Test GitHub Repositories records in your data stack.

Start with representative rows, run the joins and calculations that matter, and shape delivery around the system that will consume the data.

  1. 01

    Choose the useful scope

    Select the entities, markets, fields, dates, and business output the collection should support.

  2. 02

    Run a sample through your stack

    Check identifiers, fields, joins, missing states, and source context with your own queries or models.

  3. 03

    Set the delivery pattern

    Choose the snapshot or recurring schedule, file format, partitions, manifest, and destination.

GitHub dataset FAQ

Plan the right GitHub Repositories collection.

What does the GitHub Repositories Dataset include?

Map public GitHub repositories, organizations, releases, languages, topics, and activity for software ecosystem research. Core records include repository, organization, release, language, activity observation.

What can I build with GitHub data?

Common applications include technology ecosystem mapping, open-source project research, release and activity monitoring. Start with the fields and time window required by the business output.

How can the GitHub dataset stay current?

Use a dated ecosystem snapshot or recurring refreshes when repositories, releases, languages, and public activity need to be compared over time.

When should I use the GitHub API instead?

Use the on-demand API when your application chooses individual requests and timing. Choose this dataset for a prepared bulk snapshot or recurring file delivery.

Continue the data journey

Connect GitHub data to the wider use case.

Compare the adjacent dataset, open the source API, or continue into the relevant data, industry, and solution pages.

Start with real records

Request a GitHub dataset sample.

Tell us which repository and organization data you need, plus the markets, fields, dates, and destination. We will map the collection to that requirement.

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