Comparison
embedbase vs search
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 search if search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework.
Markdown twin · embedbase alternatives · search alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | embedbase | search |
|---|---|---|
| Maintenance | Dormant (632d since push) As of 2d · github_public_v1 | Slowing (169d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2d · github_public_v1 | Not a fork · Personal account As of 1d · 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
- search
- Go library for embedded vector search and semantic embeddings with llamacpp
Stars
- embedbase
- 523
- search
- 558
Forks
- embedbase
- 54
- search
- 24
Open issues
- embedbase
- 35
- search
- 5
Language
- embedbase
- TypeScript
- search
- Go
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.
- search
- search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework.
Persona
- embedbase
- -
- search
- -
Runtime
- embedbase
- -
- search
- -
License
- embedbase
- MIT
- search
- MIT
Last pushed
- embedbase
- Nov 27, 2024
- search
- Mar 6, 2026
Categories
- embedbase
- Data & Retrieval, Vector Databases
- search
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- embedbase
- Dormant (18%)
- search
- Slowing (36%)
Days since push
- embedbase
- 632d
- search
- 169d
Open issues (now)
- embedbase
- 35
- search
- 5
Stars delta
- embedbase
- -1 (30d)
- search
- +3 (30d)
Owner type
- embedbase
- Organization
- search
- User
Full report
- embedbase
- Trust report
- search
- Trust report
Choose embedbase if…
- embedbase is primarily TypeScript; search is Go.
- Tags unique to embedbase: artificial-intelligence, chatgpt, machine-learning, natural-language-processing.
- * 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 search if…
- search is primarily Go; embedbase is TypeScript.
- Tags unique to search: bert, gguf, gpu, llamacpp.
- Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go
When NOT to use search
- Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities
- Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution
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 (kelindar/search) · observed Aug 23, 2026
- GitHub forks (kelindar/search) · observed Aug 23, 2026
- Last push (kelindar/search) · observed Mar 6, 2026
- License file (MIT) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: embedbase 523 · search 558 (synced Aug 22, 2026).
Common questions
- What is the difference between embedbase and search?
- embedbase: A dead-simple API to build LLM-powered apps. search: Go library for embedded vector search and semantic embeddings with llamacpp. See the comparison table for live GitHub stats and shared categories.
- When should I choose embedbase over search?
- Choose embedbase over search when embedbase is primarily TypeScript; search is Go; Tags unique to embedbase: artificial-intelligence, chatgpt, machine-learning, natural-language-processing; * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase.
- When should I choose search over embedbase?
- Choose search over embedbase when search is primarily Go; embedbase is TypeScript; Tags unique to search: bert, gguf, gpu, llamacpp; Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go.
- 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 search?
- Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution
- Is embedbase or search more popular on GitHub?
- search has more GitHub stars (558 vs 523). Stars measure visibility, not whether either tool fits your constraints.
- Are embedbase and search open source?
- Yes - both are open-source projects on GitHub (embedbase: MIT, search: MIT).
- Where can I find alternatives to embedbase or search?
- GraphCanon lists graph-backed alternatives at embedbase alternatives and search alternatives (embedbase markdown twin, search 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 search?
- embedbase: Dormant. search: Slowing. 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 search?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: embedbase trust report; search trust report.