RRepoGEO

REPOGEO REPORT · LITE

zilliztech/VectorDBBench

Default branch main · commit 9871e319 · scanned 6/20/2026, 9:46:56 AM

GitHub: 1,127 stars · 396 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
67 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
2 pass · 0 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 zilliztech/VectorDBBench, 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
  • highreadme#1
    Strengthen the 'What is VDBBench' opening to emphasize it's a tool for users to run benchmarks

    Why:

    CURRENT
    VDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison.
    COPY-PASTE FIX
    VDBBench is a comprehensive, open-source benchmark tool designed for users to evaluate and compare the performance and cost-effectiveness of various vector databases and cloud services. It empowers you to reproduce results or test new systems with ease.
  • mediumcomparison#2
    Add a dedicated 'Comparison with other benchmarking tools' section

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison with other benchmarking tools' that outlines how VectorDBBench differentiates itself from other benchmark frameworks (e.g., Bench-ANN) or generic performance testing tools.
  • lowtopics#3
    Add more specific topics related to benchmarking tools and evaluation

    Why:

    CURRENT
    benchmark, cost-effectiveness, performance, vector-database, vector-search, vectordb
    COPY-PASTE FIX
    benchmark, cost-effectiveness, performance, vector-database, vector-search, vectordb, evaluation-tool, comparison-tool, open-source-benchmark, performance-testing

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
1 / 2
50% of queries surface zilliztech/VectorDBBench
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
Qdrant
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Qdrant · recommended 1×
  2. Pinecone · recommended 1×
  3. Weaviate · recommended 1×
  4. Milvus · recommended 1×
  5. Zilliz Cloud · recommended 1×
  • CATEGORY QUERY
    How can I compare performance and cost-effectiveness of various vector search databases?
    you: not recommended
    AI recommended (in order):
    1. Qdrant
    2. Pinecone
    3. Weaviate
    4. Milvus
    5. Zilliz Cloud
    6. Chroma
    7. Elasticsearch
    8. PostgreSQL
    9. pgvector

    AI recommended 9 alternatives but never named zilliztech/VectorDBBench. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tool helps evaluate and benchmark different vector databases for specific workloads?
    you: #1
    AI recommended (in order):
    1. VectorDBBench (https://github.com/zilliztech/VectorDBBench) ← you
    2. Bench-ANN (https://github.com/erikbern/ann-benchmarks)
    3. Locust (https://github.com/locustio/locust)
    4. JMeter (https://github.com/apache/jmeter)
    5. pinecone-client (https://github.com/pinecone-io/pinecone-python-client)
    6. qdrant-client (https://github.com/qdrant/qdrant-client)
    7. weaviate-client (https://github.com/weaviate/weaviate-python-client)
    8. psutil (https://github.com/giampaolo/psutil)
    9. matplotlib (https://github.com/matplotlib/matplotlib)
    10. AWS CloudWatch
    11. Azure Monitor
    12. Google Cloud Monitoring
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 zilliztech/VectorDBBench?
    pass
    AI did not name zilliztech/VectorDBBench — 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 zilliztech/VectorDBBench in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zilliztech/VectorDBBench 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 zilliztech/VectorDBBench solve, and who is the primary audience?
    pass
    AI named zilliztech/VectorDBBench explicitly

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

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zilliztech/VectorDBBench — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite