Comparison
rag_api vs memsearch
Verdict
Pick rag_api if key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration; pick memsearch if memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage.
Markdown twin · rag_api alternatives · memsearch alternatives
GraphCanon updated Sep 20, 2026
9views this month
vs
Trust & integrity
| Signal | rag_api | memsearch |
|---|---|---|
| Maintenance | Steady (35d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- rag_api
- ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
- memsearch
- A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.
Stars
- rag_api
- 901
- memsearch
- 2.6k
Forks
- rag_api
- 404
- memsearch
- 253
Open issues
- rag_api
- 45
- memsearch
- 254
Language
- rag_api
- Python
- memsearch
- Python
Adopt for
- rag_api
- Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration
- memsearch
- memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage.
Persona
- rag_api
- -
- memsearch
- -
Runtime
- rag_api
- -
- memsearch
- -
License
- rag_api
- MIT
- memsearch
- MIT
Last pushed
- rag_api
- Aug 15, 2026
- memsearch
- Sep 20, 2026
Categories
- rag_api
- Data & Retrieval, Vector Databases
- memsearch
- AI Agents, Data & Retrieval, Vector Databases
Trust and health
Maintenance
- rag_api
- Steady (60%)
- memsearch
- Very active (96%)
Days since push
- rag_api
- 35d
- memsearch
- 0d
Open issues (now)
- rag_api
- 45
- memsearch
- 254
Stars delta
- rag_api
- +35 (30d)
- memsearch
- +291 (30d)
Open issues delta
- rag_api
- -2 (30d)
- memsearch
- +23 (30d)
Owner type
- rag_api
- User
- memsearch
- Organization
Full report
- rag_api
- Trust report
- memsearch
- Trust report
Choose rag_api if…
- Tags unique to rag_api: api, api-rest, embeddings, fastapi.
- rag_api ships Docker support for self-hosted deployment.
- When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
When NOT to use rag_api
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints.
- Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
Choose memsearch if…
- Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search.
- Also covers AI Agents.
- When you need robust integration with AI agents like Claude Code or Codex
When NOT to use memsearch
- If your application doesn't require integration with specific AI agents like Claude Code
- In cases where only simple text data storage without semantic search is needed
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (danny-avila/rag_api) · observed Sep 20, 2026
- GitHub forks (danny-avila/rag_api) · observed Sep 20, 2026
- Last push (danny-avila/rag_api) · observed Aug 15, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zilliztech/memsearch) · observed Sep 20, 2026
- GitHub forks (zilliztech/memsearch) · observed Sep 20, 2026
- Last push (zilliztech/memsearch) · observed Sep 20, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: rag_api 901 · memsearch 2.6k (synced Sep 20, 2026).
Common questions
- What is the difference between rag_api and memsearch?
- rag_api: ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector. memsearch: A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.. See the comparison table for live GitHub stats and shared categories.
- When should I choose rag_api over memsearch?
- Choose rag_api over memsearch when Tags unique to rag_api: api, api-rest, embeddings, fastapi; rag_api ships Docker support for self-hosted deployment; When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
- When should I choose memsearch over rag_api?
- Choose memsearch over rag_api when Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search; Also covers AI Agents; When you need robust integration with AI agents like Claude Code or Codex.
- When should I avoid rag_api?
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints. Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
- When should I avoid memsearch?
- If your application doesn't require integration with specific AI agents like Claude Code In cases where only simple text data storage without semantic search is needed
- Is rag_api or memsearch more popular on GitHub?
- memsearch has more GitHub stars (2,627 vs 901). Stars measure visibility, not whether either tool fits your constraints.
- Are rag_api and memsearch open source?
- Yes - both are open-source projects on GitHub (rag_api: MIT, memsearch: MIT).
- Where can I find alternatives to rag_api or memsearch?
- GraphCanon lists graph-backed alternatives at rag_api alternatives and memsearch alternatives (rag_api markdown twin, memsearch 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, rag_api or memsearch?
- rag_api: Steady. memsearch: Very active. 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 rag_api and memsearch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rag_api trust report; memsearch trust report.