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    Mooncake:数据库圈的月饼反叛者,13个月被Databricks收购

    21 min
    |
    |
    May 13, 2026
    TechnologyAIEntrepreneurship

    当传统数据库在全能路线上挣扎时,Mooncake Labs 核心团队选择拥抱 Postgres 生态,仅用 13 个月便被巨头收购。本期聊聊这群大牛如何用“包月饼”的哲学解决实时分析痛点,并赢得 Databricks 的青睐。

    Mooncake:数据库圈的月饼反叛者,13个月被Databricks收购

    Best quote from Mooncake:数据库圈的月饼反叛者,13个月被Databricks收购

    “

    Mooncake 的核心价值在于减少复杂性,不再去重造轮子,而是通过一个 Postgres 扩展实现‘零 ETL’,让数据在交易型数据库和分析型湖仓之间实现亚秒级的实时同步。

    ”

    This audio lesson was created by a BeFreed community member

    Input question

    Mooncake Labs (software development and data company) - focus on its company history and founding.

    Host voices
    Lenaplay
    Lenaplay
    Learning style
    Fun
    Knowledge sources
    Mooncake is joining Databricks!
    link
    https://www.mooncake.dev/blog/mooncake-and-databricks
    Databricks Bolsters Lakebase Database ‘Vision’ With Latest Acquisition
    link
    https://www.crn.com/news/ai/2025/databricks-bolsters-lakebase-database-vision-with-latest-acquisition
    AI Launchpad 2025: Mooncake Labs
    link
    https://datacouncil.ai/talks25/ai-launchpad-2025-mooncake-labs
    Mooncake Labs joins Databricks to accelerate the vision of Lakebase
    link
    https://www.databricks.com/blog/mooncake-labs-joins-databricks-accelerate-vision-lakebase
    Mooncake-Labs/pg_mooncake
    link
    https://github.com/mooncake-labs/pg_mooncake
    Welcome to pg_mooncake | Mooncake Documentation
    link
    https://docs.mooncake.dev/pg/intro/

    Frequently Asked Questions

    Mooncake Labs 是一家由 Zhou Sun、Cheng Chen 和 Pranav Aurora 于 2024 年在旧金山创立的初创公司,在成立仅 13 个月后就被大数据巨头 Databricks 收购。其核心产品是一个名为 pg_mooncake 的 Postgres 开源扩展。这个扩展旨在打破交易型数据库(OLTP)与分析型数据库(OLAP)之间的隔阂,让开发者能够直接在熟悉的 Postgres 环境中获得高性能的实时分析能力。

    Mooncake 通过其核心组件 Moonlink(一个用 Rust 编写的库)来实现这一目标。Moonlink 作为 Postgres 的后台工作线程运行,实时监控逻辑复制日志。一旦主库有数据插入或更新,它会立即感知并将数据转换为 Apache Iceberg 开放格式,直接推送到云端对象存储(如 S3)。这种机制省去了传统架构中复杂的 ETL 管道(如 Kafka 或 Flink),实现了数据的实时同步与分析。

    AI 智能体在运行过程中会产生海量数据并需要即时反馈。传统架构由于数据搬运延迟,往往只能提供“过去的数据”,导致 AI 决策滞后。Mooncake 提供的亚秒级刷新能力让 AI 智能体能够基于实时数据进行推理和决策。此外,它整合了 DuckDB 的向量化执行能力,能够高效处理 AI 应用所需的复杂关联分析和大规模聚合查询。

    为了保证系统的稳定性,Mooncake 建议在生产环境中将 Moonlink 作为一个独立的服务运行,而不是直接作为 Postgres 内部的插件,以避免分析任务占用主数据库的 CPU 和内存资源。此外,由于数据存储在 S3 等对象存储上,数据库实际上变成了“无状态”的,这极大地增强了系统的扩展性。对于想要尝试的企业,可以先从非核心的实时监控场景开始,逐步替换原有的重型数据管道。

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    Key Takeaways

    1

    数据库世界的那个“月饼”反叛者

    0:00
    0:19
    0:41
    0:53
    1:15
    1:30
    1:49
    1:56
    2:14
    2

    当完美的理想撞上骨感的工程现实

    2:28
    2:36
    2:45
    3:11
    3:15
    3:41
    3:45
    4:02
    4:06
    4:21
    4:28
    4:49
    5:01
    3

    技术大牛们的“降维打击”

    5:24
    5:37
    5:57
    6:01
    6:21
    6:28
    6:43
    3:45
    7:07
    7:23
    7:39
    7:54
    4

    实时分析的“超能力”是如何实现的

    8:17
    8:28
    8:37
    8:39
    8:58
    9:05
    9:22
    9:28
    9:52
    9:58
    10:20
    10:27
    10:44
    10:56
    5

    当 AI Agent 遇上“懂行”的数据库

    11:25
    11:43
    11:55
    9:05
    12:25
    3:45
    7:39
    13:03
    13:19
    13:26
    13:45
    13:58
    6

    开发者和企业的“避坑指南”

    14:18
    14:32
    14:48
    9:05
    15:06
    15:09
    15:29
    15:35
    15:52
    15:57
    16:14
    16:28
    7

    从“月饼”到“湖仓”的终极融合

    16:53
    17:05
    17:09
    17:28
    17:41
    9:05
    18:19
    18:33
    18:50
    19:03
    8

    结语:在复杂世界里做那个“包月饼”的人

    19:19
    19:35
    18:50
    20:04
    20:20
    20:38
    20:43
    20:54
    21:00
    21:07
    21:16

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