Comparison
embedbase vs chromem-go
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 chromem-go if chromem-go is an embeddable vector database for Go that provides a Chroma-like interface with no third-party dependencies, suitable for applications needing in-memory persistence and cosine similarity search capabilities.
Markdown twin · embedbase alternatives · chromem-go alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | embedbase | chromem-go |
|---|---|---|
| Maintenance | Dormant (601d since push) As of 1mo · github_public_v1 | Slowing (96d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1mo · github_public_v1 | Not a fork · Personal account As of today · 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
- chromem-go
- Embeddable vector database for Go with Chroma-like interface.
Stars
- embedbase
- 524
- chromem-go
- 1.0k
Forks
- embedbase
- 55
- chromem-go
- 75
Open issues
- embedbase
- 35
- chromem-go
- 18
Language
- embedbase
- TypeScript
- chromem-go
- 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.
- chromem-go
- Chromem-go is an embeddable vector database for Go that provides a Chroma-like interface with no third-party dependencies, suitable for applications needing in-memory persistence and cosine similarity search capabilities
Persona
- embedbase
- -
- chromem-go
- -
Runtime
- embedbase
- -
- chromem-go
- -
License
- embedbase
- MIT
- chromem-go
- MPL-2.0
Last pushed
- embedbase
- Nov 27, 2024
- chromem-go
- May 17, 2026
Categories
- embedbase
- Data & Retrieval, Vector Databases
- chromem-go
- Vector Databases
Trust and health
Maintenance
- embedbase
- Dormant (18%)
- chromem-go
- Slowing (36%)
Days since push
- embedbase
- 601d
- chromem-go
- 96d
Open issues (now)
- embedbase
- 35
- chromem-go
- 18
Stars delta
- embedbase
- Unknown
- chromem-go
- +14 (30d)
Open issues delta
- embedbase
- Unknown
- chromem-go
- +1 (30d)
Owner type
- embedbase
- Organization
- chromem-go
- User
Full report
- embedbase
- Trust report
- chromem-go
- Trust report
Choose embedbase if…
- embedbase is primarily TypeScript; chromem-go is Go.
- License: embedbase is MIT, chromem-go is MPL-2.0.
- Tags unique to embedbase: ai, artificial-intelligence, chatgpt, machine-learning.
- 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 chromem-go if…
- chromem-go is primarily Go; embedbase is TypeScript.
- License: chromem-go is MPL-2.0, embedbase is MIT.
- Requirements: Min 0.5 GB RAM.
- Tags unique to chromem-go: chroma, cosine-similarity, in-memory, llms.
- If you are building applications in Go and require an in-memory vector database without additional third-party libraries.
When NOT to use chromem-go
- Avoid Chromem-go if you seek a traditional, disk-based persistence model as it primarily supports in-memory operations with optional persistence options.
- Chromem-go is not the best choice if your application requires heavy concurrent load and large-scale data handling which might surpass the in-memory capability limits of this library.
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 Jul 22, 2026
- GitHub forks (different-ai/embedbase) · observed Jul 22, 2026
- Last push (different-ai/embedbase) · observed Nov 27, 2024
- License file (MIT) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (philippgille/chromem-go) · observed Aug 21, 2026
- GitHub forks (philippgille/chromem-go) · observed Aug 21, 2026
- Last push (philippgille/chromem-go) · observed May 17, 2026
- License file (MPL-2.0) · observed Aug 21, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: embedbase 524 · chromem-go 1.0k (synced Jul 22, 2026).
Common questions
- What is the difference between embedbase and chromem-go?
- embedbase: A dead-simple API to build LLM-powered apps. chromem-go: Embeddable vector database for Go with Chroma-like interface.. See the comparison table for live GitHub stats and shared categories.
- When should I choose embedbase over chromem-go?
- Choose embedbase over chromem-go when embedbase is primarily TypeScript; chromem-go is Go; License: embedbase is MIT, chromem-go is MPL-2.0; Tags unique to embedbase: ai, artificial-intelligence, chatgpt, machine-learning; 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 chromem-go over embedbase?
- Choose chromem-go over embedbase when chromem-go is primarily Go; embedbase is TypeScript; License: chromem-go is MPL-2.0, embedbase is MIT; Requirements: Min 0.5 GB RAM; Tags unique to chromem-go: chroma, cosine-similarity, in-memory, llms; If you are building applications in Go and require an in-memory vector database without additional third-party libraries.
- 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 chromem-go?
- Avoid Chromem-go if you seek a traditional, disk-based persistence model as it primarily supports in-memory operations with optional persistence options. Chromem-go is not the best choice if your application requires heavy concurrent load and large-scale data handling which might surpass the in-memory capability limits of this library.
- Is embedbase or chromem-go more popular on GitHub?
- chromem-go has more GitHub stars (1,047 vs 524). Stars measure visibility, not whether either tool fits your constraints.
- Are embedbase and chromem-go open source?
- Yes - both are open-source projects on GitHub (embedbase: MIT, chromem-go: MPL-2.0).
- Where can I find alternatives to embedbase or chromem-go?
- GraphCanon lists graph-backed alternatives at embedbase alternatives and chromem-go alternatives (embedbase markdown twin, chromem-go 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 chromem-go?
- embedbase: Dormant. chromem-go: 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 chromem-go?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: embedbase trust report; chromem-go trust report.