Comparison
embedbase vs lantern
Verdict
Pick embedbase if embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases; pick lantern if lantern is an extension for PostgreSQL written in Rust, providing capabilities for approximate nearest neighbor search tailored for AI applications.
Markdown twin · embedbase alternatives · lantern alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | embedbase | lantern |
|---|---|---|
| Maintenance | Dormant (632d since push) As of 2d · github_public_v1 | Dormant (618d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2d · github_public_v1 | Not a fork · Organization account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- embedbase
- A dead-simple API to build LLM-powered apps
- lantern
- PostgreSQL vector database extension for building AI applications
Stars
- embedbase
- 523
- lantern
- 889
Forks
- embedbase
- 54
- lantern
- 67
Open issues
- embedbase
- 35
- lantern
- 42
Language
- embedbase
- TypeScript
- lantern
- Rust
Adopt for
- embedbase
- Embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases.
- lantern
- Lantern is an extension for PostgreSQL written in Rust, providing capabilities for approximate nearest neighbor search tailored for AI applications.
Persona
- embedbase
- -
- lantern
- -
Runtime
- embedbase
- -
- lantern
- -
License
- embedbase
- MIT
- lantern
- AGPL-3.0, allowing free use and modification but requiring derivative works to be open-sourced as well.
Last pushed
- embedbase
- Nov 27, 2024
- lantern
- Dec 12, 2024
Categories
- embedbase
- Data & Retrieval, Vector Databases
- lantern
- Vector Databases
Trust and health
Days since push
- embedbase
- 632d
- lantern
- 618d
Open issues (now)
- embedbase
- 35
- lantern
- 42
Stars delta
- embedbase
- -1 (30d)
- lantern
- 0 (30d)
Full report
- embedbase
- Trust report
- lantern
- Trust report
Choose embedbase if…
- embedbase is primarily TypeScript; lantern is Rust.
- License: embedbase is MIT, lantern is AGPL-3.0.
- Tags unique to embedbase: artificial-intelligence, chatgpt, natural-language-processing, openai.
- Also covers Data & Retrieval.
- * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase.
When NOT to use embedbase
- * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python.
- * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers.
Choose lantern if…
- lantern is primarily Rust; embedbase is TypeScript.
- License: lantern is AGPL-3.0, embedbase is MIT.
- Tags unique to lantern: ann, approximate-nearest-neighbor-search, data-science, hnsw.
- When you need to perform vector database operations integrated with a PostgreSQL environment
When NOT to use lantern
- Avoid when an open-source license like AGPL-3.0 might interfere with proprietary or closed-source projects
- Not suitable if you require direct support for non-vector indexing operations outside ANN capabilities
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (different-ai/embedbase) · observed Aug 22, 2026
- GitHub forks (different-ai/embedbase) · observed Aug 22, 2026
- Last push (different-ai/embedbase) · observed Nov 27, 2024
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (lanterndata/lantern) · observed Aug 22, 2026
- GitHub forks (lanterndata/lantern) · observed Aug 22, 2026
- Last push (lanterndata/lantern) · observed Dec 12, 2024
- License file (AGPL-3.0) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: embedbase 523 · lantern 889 (synced Aug 22, 2026).
Common questions
- What is the difference between embedbase and lantern?
- embedbase: A dead-simple API to build LLM-powered apps. lantern: PostgreSQL vector database extension for building AI applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose embedbase over lantern?
- Choose embedbase over lantern when embedbase is primarily TypeScript; lantern is Rust; License: embedbase is MIT, lantern is AGPL-3.0; Tags unique to embedbase: artificial-intelligence, chatgpt, natural-language-processing, openai; Also covers Data & Retrieval; * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase.
- When should I choose lantern over embedbase?
- Choose lantern over embedbase when lantern is primarily Rust; embedbase is TypeScript; License: lantern is AGPL-3.0, embedbase is MIT; Tags unique to lantern: ann, approximate-nearest-neighbor-search, data-science, hnsw; When you need to perform vector database operations integrated with a PostgreSQL environment.
- When should I avoid embedbase?
- * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python. * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers.
- When should I avoid lantern?
- Avoid when an open-source license like AGPL-3.0 might interfere with proprietary or closed-source projects Not suitable if you require direct support for non-vector indexing operations outside ANN capabilities
- Is embedbase or lantern more popular on GitHub?
- lantern has more GitHub stars (889 vs 523). Stars measure visibility, not whether either tool fits your constraints.
- Are embedbase and lantern open source?
- Yes - both are open-source projects on GitHub (embedbase: MIT, lantern: AGPL-3.0).
- Where can I find alternatives to embedbase or lantern?
- GraphCanon lists graph-backed alternatives at embedbase alternatives and lantern alternatives (embedbase markdown twin, lantern markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, embedbase or lantern?
- embedbase: Dormant. lantern: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for embedbase and lantern?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: embedbase trust report; lantern trust report.