RRepoGEO

REPOGEO REPORT · LITE

sql-machine-learning/sqlflow

Default branch develop · commit 6c492098 · scanned 5/9/2026, 9:12:37 PM

GitHub: 5,186 stars · 705 forks

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 README's "What is SQLFlow" section for clarity

    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 compiler that extends SQL to enable machine learning tasks (training, prediction, explanation) and mathematical programming. It transforms SQL programs with AI extensions into distributed workflows, primarily running on Kubernetes using Argo Workflows, making MLOps accessible directly from your database.
  • mediumtopics#2
    Add more specific topics to improve category visibility

    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, sql-compiler, mlops, kubernetes-workflows, argo-workflows, declarative-ml
  • lowcomparison#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README titled 'Comparison with Managed ML Services' or 'SQLFlow vs. BigQuery ML / Databricks SQL' that highlights SQLFlow's role as an open-source, Kubernetes-native compiler for extending SQL with ML, contrasting it with proprietary, cloud-specific, or general-purpose data platforms.

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
Databricks SQL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Databricks SQL · recommended 2×
  2. BigQuery ML · recommended 1×
  3. SQL Server Machine Learning Services · recommended 1×
  4. PostgreSQL · recommended 1×
  5. Oracle Machine Learning · recommended 1×
  • CATEGORY QUERY
    How can I integrate machine learning model training directly into my SQL queries?
    you: not recommended
    AI recommended (in order):
    1. BigQuery ML
    2. SQL Server Machine Learning Services
    3. PostgreSQL
    4. Oracle Machine Learning
    5. Snowflake
    6. Databricks SQL
    7. MLflow
    8. DuckDB

    AI recommended 8 alternatives but never named sql-machine-learning/sqlflow. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to run distributed AI predictions and training using familiar SQL syntax on Kubernetes?
    you: not recommended
    AI recommended (in order):
    1. Apache Spark
    2. Trino
    3. ClickHouse
    4. Materialize
    5. Databricks SQL
    6. Apache Flink

    AI recommended 6 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?

Embed your GEO score

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MARKDOWN (README)
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