RRepoGEO

REPOGEO REPORT · LITE

sql-machine-learning/sqlflow

Default branch develop · commit 6c492098 · scanned 6/19/2026, 6:37:44 PM

GitHub: 5,183 stars · 703 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
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 sql-machine-learning/sqlflow, 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
    Reposition the 'What is SQLFlow' section to clarify its unique role

    Why:

    CURRENT
    SQLFlow is a compiler that compiles a SQL program to a workflow that runs on Kubernetes. The input is a SQL program that written in our extended SQL grammar to support AI jobs including training, prediction, model evaluation, model explanation, custom jobs, and mathematical programming. The output is an Argo workflow that runs on a Kubernetes cluster distributed.
    COPY-PASTE FIX
    SQLFlow is an open-source **SQL extension and compiler** that enables data professionals to **define and execute end-to-end machine learning workflows directly within SQL queries**. It translates your extended SQL programs into distributed workflows (like Argo Workflows) that run on Kubernetes, bridging the gap between SQL databases and modern AI platforms without requiring separate programming languages.
  • mediumabout#2
    Update the repository's 'About' description for clarity

    Why:

    CURRENT
    Brings SQL and AI together.
    COPY-PASTE FIX
    An open-source SQL extension and compiler that enables defining and executing end-to-end machine learning workflows directly within SQL queries, translating them into distributed jobs on Kubernetes.
  • mediumtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    ai, databases, deep-learning, machine-learning, sql-syntax, sqlflow, transpiler
    COPY-PASTE FIX
    ai, databases, deep-learning, machine-learning, sql-syntax, sqlflow, transpiler, kubernetes-ml, sql-for-ml, ml-workflows, sql-compiler

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 sql-machine-learning/sqlflow
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SQL Server Machine Learning Services
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SQL Server Machine Learning Services · recommended 1×
  2. PostgreSQL · recommended 1×
  3. Apache MADlib · recommended 1×
  4. Oracle Machine Learning (OML) for SQL · recommended 1×
  5. Teradata Vantage · recommended 1×
  • CATEGORY QUERY
    How can I run machine learning training jobs directly within my SQL database environment?
    you: not recommended
    AI recommended (in order):
    1. SQL Server Machine Learning Services
    2. PostgreSQL
    3. Apache MADlib
    4. Oracle Machine Learning (OML) for SQL
    5. Teradata Vantage
    6. Google BigQuery ML
    7. Snowflake
    8. Snowpark
    9. External Functions

    AI recommended 9 alternatives but never named sql-machine-learning/sqlflow. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow defining and executing AI workflows using SQL syntax on Kubernetes?
    you: not recommended
    AI recommended (in order):
    1. KubeFlow Pipelines
    2. Kale
    3. Apache Airflow
    4. KubernetesExecutor
    5. Argo Workflows
    6. Prefect
    7. Kubernetes Agent
    8. Dagster

    AI recommended 8 alternatives but never named sql-machine-learning/sqlflow. 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 sql-machine-learning/sqlflow?
    pass
    AI named sql-machine-learning/sqlflow explicitly

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

  • If a team adopts sql-machine-learning/sqlflow in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sql-machine-learning/sqlflow 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 sql-machine-learning/sqlflow solve, and who is the primary audience?
    pass
    AI named sql-machine-learning/sqlflow 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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