RRepoGEO

REPOGEO REPORT · LITE

getdozer/dozer

Default branch main · commit 8b0b4cc0 · scanned 5/27/2026, 4:06:32 AM

GitHub: 1,576 stars · 136 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 getdozer/dozer, 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 opening paragraph to assert category and differentiation

    Why:

    CURRENT
    ## Overview
    
    Dozer is a **real time data movement tool leveraging CDC from various sources to multiple sinks.**
    
    Dozer is magnitudes of times faster than Debezium+Kafka and natively supports stateless transformations. 
    Primarily used for moving data into warehouses. In our own application, we move data to **Clickhouse** and build data APIs and integration with LLMs.
    COPY-PASTE FIX
    ## Overview
    
    Dozer is an **open-source real-time data integration and CDC platform** that moves data from various sources to multiple sinks, enabling instant data APIs and materialized views. It's designed as a faster, more flexible alternative to traditional CDC tools like Debezium combined with streaming platforms, primarily used for moving data into warehouses and building data APIs and integration with LLMs.
  • hightopics#2
    Add specific topics for CDC, data integration, and ETL/ELT tools

    Why:

    CURRENT
    api, apis, clickhouse, data, datawarehouse, debe, etl, low-code, postgres, realtime, rust, snowflake, sql, streaming
    COPY-PASTE FIX
    api, apis, cdc, clickhouse, data, data-integration, data-pipeline, datawarehouse, debe, elt-tool, etl, etl-tool, low-code, postgres, realtime, rust, snowflake, sql, streaming
  • mediumabout#3
    Refine the repository description for better keyword alignment

    Why:

    CURRENT
    Dozer is a real-time data movement tool that leverages CDC from various sources and moves data into various sinks.
    COPY-PASTE FIX
    Dozer is an open-source real-time data integration and CDC platform for building instant data APIs and materialized views, moving data from databases and streams to data warehouses and other sinks.

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 getdozer/dozer
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
apache/kafka
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/kafka · recommended 2×
  2. Debezium · recommended 1×
  3. Fivetran · recommended 1×
  4. Striim · recommended 1×
  5. Qlik Replicate · recommended 1×
  • CATEGORY QUERY
    How to move data in real-time from databases to a data warehouse using change data capture?
    you: not recommended
    AI recommended (in order):
    1. Debezium
    2. Fivetran
    3. Striim
    4. Qlik Replicate
    5. AWS Database Migration Service (DMS)
    6. Google Cloud Dataflow
    7. Azure Data Factory

    AI recommended 7 alternatives but never named getdozer/dozer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a fast tool for real-time data integration and building APIs from streaming sources.
    you: not recommended
    AI recommended (in order):
    1. Apache Kafka (apache/kafka)
    2. Kafka Streams (apache/kafka)
    3. ksqlDB (confluentinc/ksqldb)
    4. Confluent Platform
    5. Confluent Cloud
    6. Apache Flink (apache/flink)
    7. Materialize (MaterializeInc/materialize)
    8. Decodable
    9. Redpanda (redpanda-data/redpanda)

    AI recommended 9 alternatives but never named getdozer/dozer. 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 getdozer/dozer?
    pass
    AI named getdozer/dozer explicitly

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

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

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

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