RRepoGEO

REPOGEO REPORT · LITE

risingwavelabs/risingwave

Default branch main · commit a10c7cdc · scanned 6/22/2026, 6:41:24 AM

GitHub: 9,092 stars · 778 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
59 /100
Needs work
Category recall
1 / 2
Avg rank #6.0 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
  • highreadme#1
    Strengthen README opening to emphasize unique value for AI agents

    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 the unified 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. Unlike traditional complex stacks (e.g., Debezium + Kafka + Flink + serving DB), RisingWave provides a single, PostgreSQL-compatible system specifically designed to power real-time AI agents with continuously updated materialized views.
  • mediumabout#2
    Enhance repository description to highlight AI agent value proposition

    Why:

    CURRENT
    Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
    COPY-PASTE FIX
    The unified event streaming platform for agentic AI. Ingest, transform, and serve real-time data streams at scale, powering AI agents with continuously updated materialized views and a PostgreSQL-compatible SQL interface.
  • mediumtopics#3
    Add specific AI-related 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, agentic-ai, real-time-ai, ai-data-platform

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
#6.0
Lower is better. #1 = top recommendation.
Share of voice
8%
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. apache/flink · recommended 2×
  3. Confluent Platform · recommended 1×
  4. Google Cloud Pub/Sub · recommended 1×
  5. Amazon Kinesis · recommended 1×
  • CATEGORY QUERY
    I need an event streaming platform for real-time data ingestion and transformation for AI agents.
    you: not recommended
    AI recommended (in order):
    1. Apache Kafka (apache/kafka)
    2. Confluent Platform
    3. Apache Flink (apache/flink)
    4. Google Cloud Pub/Sub
    5. Amazon Kinesis
    6. Azure Event Hubs
    7. Redpanda (redpanda-data/redpanda)

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

    Show full AI answer
  • CATEGORY QUERY
    Looking for a stream processing engine to build real-time materialized views from diverse data sources.
    you: #6
    AI recommended (in order):
    1. Apache Flink (apache/flink)
    2. Apache Kafka Streams (apache/kafka)
    3. Materialize (MaterializeInc/materialize)
    4. Apache Spark Structured Streaming (apache/spark)
    5. ksqlDB (confluentinc/ksql)
    6. RisingWave (risingwavelabs/risingwave) ← you
    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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risingwavelabs/risingwave — 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