RRepoGEO

REPOGEO REPORT · LITE

VexDB-THU/VexDB-Lite

Default branch main · commit 9416e62b · scanned 6/17/2026, 3:51:18 AM

GitHub: 551 stars · 104 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface VexDB-THU/VexDB-Lite, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to the repository

    Why:

    COPY-PASTE FIX
    ["vector-database", "vector-search", "approximate-nearest-neighbor", "ann-index", "postgresql-extension", "duckdb-extension", "similarity-search", "embedding", "hnsw"]
  • highreadme#2
    Strengthen the README's opening statement and H1

    Why:

    CURRENT
    # VexDB

`VexDB-Lite` is a vector similarity search engine for PostgreSQL (`vexdb_lite` extension) and DuckDB (`vexdb_lite` extension).
    COPY-PASTE FIX
    # VexDB-Lite: A Vector Similarity Search Engine for PostgreSQL and DuckDB

VexDB-Lite is a cross-platform vector database designed as a plugin for existing databases, specifically providing efficient vector similarity search capabilities and approximate nearest neighbor (ANN) indexing for PostgreSQL and DuckDB.
  • mediumabout#3
    Refine the repository description for clarity

    Why:

    CURRENT
    A cross-platform vector database, which can be integrated into existing databases as a plugin.
    COPY-PASTE FIX
    VexDB-Lite is a cross-platform vector database plugin, providing efficient vector similarity search and approximate nearest neighbor (ANN) indexing for PostgreSQL and DuckDB.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface VexDB-THU/VexDB-Lite
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pgvector
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. pgvector · recommended 1×
  2. Lantern · recommended 1×
  3. pg_embedding · recommended 1×
  4. TimescaleDB · recommended 1×
  5. Neon · recommended 1×
  • CATEGORY QUERY
    How to add vector similarity search capabilities directly into an existing PostgreSQL database?
    you: not recommended
    AI recommended (in order):
    1. pgvector
    2. Lantern
    3. pg_embedding
    4. TimescaleDB
    5. Neon

    AI recommended 5 alternatives but never named VexDB-THU/VexDB-Lite. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an efficient approximate nearest neighbor index for vector embeddings in DuckDB.
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Hnswlib
    3. ScaNN
    4. Annoy
    5. Milvus

    AI recommended 5 alternatives but never named VexDB-THU/VexDB-Lite. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of VexDB-THU/VexDB-Lite?
    pass
    AI did not name VexDB-THU/VexDB-Lite — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts VexDB-THU/VexDB-Lite in production, what risks or prerequisites should they evaluate first?
    pass
    AI named VexDB-THU/VexDB-Lite explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo VexDB-THU/VexDB-Lite solve, and who is the primary audience?
    pass
    AI named VexDB-THU/VexDB-Lite explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of VexDB-THU/VexDB-Lite. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/VexDB-THU/VexDB-Lite.svg)](https://repogeo.com/en/r/VexDB-THU/VexDB-Lite)
HTML
<a href="https://repogeo.com/en/r/VexDB-THU/VexDB-Lite"><img src="https://repogeo.com/badge/VexDB-THU/VexDB-Lite.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

VexDB-THU/VexDB-Lite — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite