RRepoGEO

REPOGEO REPORT · LITE

pingcap/tiflash

Default branch master · commit ed4e382d · scanned 5/13/2026, 6:32:17 AM

GitHub: 1,018 stars · 415 forks

AI VISIBILITY SCORE
35 /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
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 pingcap/tiflash, 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

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

OVERALL DIRECTION
  • highreadme#1
    Emphasize TiFlash's role as a distributed columnar HTAP database in the README's opening

    Why:

    CURRENT
    # TiFlash

TiFlash is a columnar storage component of TiDB and TiDB Cloud, the fully-managed service of TiDB. It mainly plays the role of Analytical Processing (AP) in the Hybrid Transactional/Analytical Processing (HTAP) architecture of TiDB.
    COPY-PASTE FIX
    # TiFlash: A Distributed Columnar HTAP Database Engine

TiFlash is the analytical engine for TiDB and TiDB Cloud, designed for Hybrid Transactional/Analytical Processing (HTAP). It provides real-time analytical processing on transactional data by acting as a distributed columnar storage component within the TiDB ecosystem, leveraging Massively Parallel Processing (MPP) for accelerating complex analytical queries.
  • mediumcomparison#2
    Add a comparison section to clarify positioning against similar solutions

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., "TiFlash vs. Other Analytical Solutions" or "Why TiFlash for HTAP?", that explicitly compares TiFlash's integrated HTAP approach within TiDB against standalone columnar databases (like ClickHouse, Snowflake) or streaming analytics platforms (like Flink, Druid). Highlight its real-time transactional consistency and seamless integration with TiDB's OLTP layer.

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 pingcap/tiflash
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apache Flink
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Apache Flink · recommended 1×
  2. Apache Kafka · recommended 1×
  3. ksqlDB · recommended 1×
  4. Apache Druid · recommended 1×
  5. ClickHouse · recommended 1×
  • CATEGORY QUERY
    What are good solutions for real-time analytical processing on transactional data?
    you: not recommended
    AI recommended (in order):
    1. Apache Flink
    2. Apache Kafka
    3. ksqlDB
    4. Apache Druid
    5. ClickHouse
    6. Materialize
    7. Rockset

    AI recommended 7 alternatives but never named pingcap/tiflash. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a distributed columnar database with MPP for accelerating complex analytical queries.
    you: not recommended
    AI recommended (in order):
    1. Snowflake
    2. Amazon Redshift
    3. Google BigQuery
    4. ClickHouse (ClickHouse/ClickHouse)
    5. Azure Synapse Analytics
    6. Vertica

    AI recommended 6 alternatives but never named pingcap/tiflash. 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 pingcap/tiflash?
    pass
    AI named pingcap/tiflash explicitly

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

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

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

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pingcap/tiflash — 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