RRepoGEO

REPOGEO REPORT · LITE

databendlabs/databend

Default branch main · commit cae68306 · scanned 6/26/2026, 4:57:01 AM

GitHub: 9,356 stars · 886 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)

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

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 databendlabs/databend, 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
  • highabout#1
    Update repository description to emphasize unified capabilities for AI agents

    Why:

    CURRENT
    Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.
    COPY-PASTE FIX
    Databend: The Enterprise Data Warehouse for AI Agents. Unifies large-scale analytics, vector search, and full-text search with secure Python UDFs for agent orchestration, all on your S3.
  • mediumreadme#2
    Integrate 'high-performance' and 'unified' into README's opening paragraph

    Why:

    CURRENT
    Large-scale analytics, vector search, full-text search — with flexible agent orchestration and secure Python UDF sandboxes. Built for enterprise AI workloads.
    COPY-PASTE FIX
    A high-performance, enterprise data warehouse for AI Agents, Databend unifies large-scale analytics, vector search, and full-text search with flexible agent orchestration and secure Python UDF sandboxes. Built for modern enterprise AI workloads.
  • lowlicense#3
    Add explicit license clarification to README

    Why:

    COPY-PASTE FIX
    ## License
Databend is licensed under [insert specific license(s) here, e.g., Apache 2.0 and other components]. Please refer to the [LICENSE](LICENSE) file for complete details.

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 databendlabs/databend
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Snowflake
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Snowflake · recommended 2×
  2. Databricks · recommended 1×
  3. Google Cloud · recommended 1×
  4. Azure · recommended 1×
  5. SingleStoreDB · recommended 1×
  • CATEGORY QUERY
    What data platform unifies analytics, vector search, and AI agent orchestration with Python UDFs?
    you: not recommended
    AI recommended (in order):
    1. Databricks
    2. Snowflake
    3. Google Cloud
    4. Azure
    5. SingleStoreDB
    6. Rockset
    7. ClickHouse
    8. Milvus
    9. Pinecone
    10. LangChain
    11. LlamaIndex

    AI recommended 11 alternatives but never named databendlabs/databend. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performance, cloud-native data warehouse for large-scale analytics and full-text search.
    you: not recommended
    AI recommended (in order):
    1. Snowflake
    2. Elasticsearch (elastic/elasticsearch)
    3. OpenSearch (opensearch-project/OpenSearch)
    4. Google BigQuery
    5. Cloud Search
    6. Datastore
    7. Amazon Redshift
    8. Amazon OpenSearch Service
    9. ClickHouse (ClickHouse/ClickHouse)
    10. Altinity.Cloud
    11. ClickHouse Cloud
    12. Azure Synapse Analytics
    13. Azure Cognitive Search

    AI recommended 13 alternatives but never named databendlabs/databend. This is the gap to close.

    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 databendlabs/databend?
    pass
    AI named databendlabs/databend explicitly

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

  • If a team adopts databendlabs/databend in production, what risks or prerequisites should they evaluate first?
    pass
    AI named databendlabs/databend 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 databendlabs/databend solve, and who is the primary audience?
    pass
    AI named databendlabs/databend explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
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