RRepoGEO

REPOGEO REPORT · LITE

risingwavelabs/risingwave

Default branch main · commit 15c9aa20 · scanned 5/12/2026, 12:31:15 AM

GitHub: 8,999 stars · 767 forks

AI VISIBILITY SCORE
71 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
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 risingwavelabs/risingwave, 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
  • hightopics#1
    Add 'ai' and 'agentic-ai' to repository topics

    Why:

    CURRENT
    apache-iceberg, data-engineering, database, etl-pipeline, event-streaming, kafka, materialized-view, postgresql, rust, stream-processing, webhook
    COPY-PASTE FIX
    apache-iceberg, data-engineering, database, etl-pipeline, event-streaming, kafka, materialized-view, postgresql, rust, stream-processing, webhook, ai, agentic-ai
  • mediumhomepage#2
    Update homepage URL to main project website

    Why:

    CURRENT
    https://go.risingwave.com/slack
    COPY-PASTE FIX
    https://risingwave.com
  • lowreadme#3
    Elaborate on RisingWave's specific value for agentic AI applications

    Why:

    CURRENT
    RisingWave is an event streaming platform for agentic AI. It continuously ingests data from databases, event streams, and webhooks, processes it incrementally, and serves fresh results at low latency, replacing the traditional event streaming stack (e.g., Debezium + Kafka + Flink + serving DB) with a single system.
    COPY-PASTE FIX
    RisingWave is an event streaming platform for agentic AI. It continuously ingests data from databases, event streams, and webhooks, processes it incrementally, and serves fresh results at low latency, replacing the traditional event streaming stack (e.g., Debezium + Kafka + Flink + serving DB) with a single system. This enables AI agents to access the freshest context and react in real time, powering dynamic decision-making and personalized experiences.

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
1 / 2
50% of queries surface risingwavelabs/risingwave
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
apache/flink
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/flink · recommended 2×
  2. apache/kafka · recommended 1×
  3. confluentinc/ksqldb · recommended 1×
  4. Databricks · recommended 1×
  5. Confluent Platform · recommended 1×
  • CATEGORY QUERY
    What tools continuously ingest and process event streams for real-time AI applications at scale?
    you: not recommended
    AI recommended (in order):
    1. Apache Flink (apache/flink)
    2. Apache Kafka Streams (apache/kafka)
    3. ksqlDB (confluentinc/ksqldb)
    4. Databricks
    5. Confluent Platform
    6. Amazon Kinesis Data Analytics
    7. Google Cloud Dataflow

    AI recommended 7 alternatives but never named risingwavelabs/risingwave. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a real-time stream processing platform that uses materialized views instead of complex Kafka setups.
    you: #2
    AI recommended (in order):
    1. Materialize (MaterializeInc/materialize)
    2. RisingWave (risingwavelabs/risingwave) ← you
    3. Apache Flink (apache/flink)
    4. ClickHouse (ClickHouse/ClickHouse)
    5. Apache Druid (apache/druid)
    6. Tinybird
    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 risingwavelabs/risingwave?
    pass
    AI named risingwavelabs/risingwave explicitly

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

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

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

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