Elasticsearch

license

AGPL-3.0(OSI)

enterprise-dir

Elastic-License-2.0

source

public

core-gated

gated(the x-pack directory is licensed solely under the Elastic License 2.0 rather than the repository's default triple license, so a set of features in the published tree cannot be run under the open terms)

AGPL-3.0 license body confirmed. The LICENSE body sets a default triple license - AGPL-3.0 only, SSPL-1.0 or Elastic License 2.0, at the recipient's choice - so an OSI branch is available for the bulk of the tree, and AGPL-3.0 is the tier this records. It then carves out the x-pack directory as Elastic License 2.0 alone, and that directory is present in the repository. Functionality withheld from the open terms inside the published source is what the ladder calls a gated core, the same shape as litellm's enterprise directory rather than a separate hosted service sold beside a complete core.

• https://github.com/elastic/elasticsearch/blob/main/LICENSE.txt recorded 2026-08-18

  LICENSE.txt states the default is a triple license - GNU Affero General Public License v3.0 only, Server Side Public License v1, and Elastic License 2.0 - and that code licensed solely under the Elastic License 2.0 is found only in the x-pack folder, which is present in the repository root.

• https://api.github.com/repos/elastic/elasticsearch recorded 2026-08-18

  Repo metadata - license spdx_id NOASSERTION, private false, archived false, default branch main - for elastic/elasticsearch.

• https://github.com/elastic/elasticsearch/blob/main/README.asciidoc recorded 2026-08-18

  README describes a distributed search and analytics engine, data store and vector database, with retrieval-augmented generation, vector search and full-text search among its listed use cases, and names the separately licensed portion of the same repository rather than presenting the tree as uniformly open.

77,824 GitHub stars, which lands in the >10K stars band of the stars scale, level 3. The `elasticsearch` package on PyPI is the Python client (elasticsearch-py), not the server, so its 52.8M monthly downloads measure client installs and cannot be attributed to this product. Elastic publishes no server deployment count, so the stars scale applies and caps the band at 3 despite the size of the install base.

• https://api.github.com/repos/elastic/elasticsearch recorded 2026-08-18

  Repo metadata - stargazers_count = 77,824 - for elastic/elasticsearch.

Level with vespa at the top of the storage feature matrix, which bands on how much of the persist-index-retrieve path a product provides itself, at what scale and over how many retrieval modes. The 5 rung is for a distributed platform that also hosts and evaluates ranking or embedding models inside the serving path, and Elasticsearch does: the `inference`, `ml` and `ml-package-loader` plugins ship in the repository beside `rank-rrf` and `rank-vectors`. That is the line between this rung and the 4 rung the vector databases sit on, which fuse or filter scores but host no model. Worth reading beside the openness score: the plugins that earn this band live in x-pack, the Elastic-License-only directory that makes the product open_core rather than open_source.

• https://github.com/elastic/elasticsearch/blob/main/README.asciidoc recorded 2026-08-18

  README still documents a distributed search and analytics engine, data store and vector database, with retrieval-augmented generation, vector search and full-text search among its listed use cases.

• https://api.github.com/repos/elastic/elasticsearch/contents/x-pack/plugin recorded 2026-08-18

  x-pack/plugin tree: `inference`, `ml` and `ml-package-loader` plugins ship in the repository beside `rank-rrf` and `rank-vectors`, so model hosting, inference endpoints and reranking are part of the engine rather than a separate product. They sit inside x-pack, which is the Elastic-License-only directory this product's openness score records as its gate.