<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>数据库工程博客</title><link>https://stdb.top/</link><description>Recent content on 数据库工程博客</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Sun, 05 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://stdb.top/index.xml" rel="self" type="application/rss+xml"/><item><title>Lakehouse 系列总览</title><link>https://stdb.top/lakehouse-series/lakehouse-series-overview/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/lakehouse-series-overview/</guid><description>先理解 lakehouse 到底解决什么问题，再进入表格式、摄入链路、计算成本和治理等具体主题。</description></item><item><title>云数据库系列总览</title><link>https://stdb.top/cloud-database-series/cloud-database-series-overview/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/cloud-database-series-overview/</guid><description>云数据库系列总览，适合先建立整体阅读地图，再进入选型、稳定性、性能、成本与迁移等具体主题。</description></item><item><title>第 1 篇：Lakehouse 到底在解决什么问题</title><link>https://stdb.top/lakehouse-series/what-lakehouse-solves/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/what-lakehouse-solves/</guid><description>从平台边界而不是产品名词的角度理解 lakehouse，避免把它误当成“更便宜的数据仓库”。</description></item><item><title>第 1 篇：云数据库到底改变了什么</title><link>https://stdb.top/cloud-database-series/what-cloud-database-changed/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/what-cloud-database-changed/</guid><description>从责任边界变化的角度理解云数据库，适合团队在上云前先判断哪些事情被平台接管，哪些仍要自己负责。</description></item><item><title>第 2 篇：Iceberg、Delta Lake、Hudi 该怎么看</title><link>https://stdb.top/lakehouse-series/lakehouse-table-format-selection/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/lakehouse-table-format-selection/</guid><description>从写入模式、读写并发、元数据管理和引擎兼容性四个角度讨论 lakehouse 表格式选择。</description></item><item><title>第 2 篇：关系型、NoSQL、NewSQL 怎么选</title><link>https://stdb.top/cloud-database-series/how-to-choose-cloud-database/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/how-to-choose-cloud-database/</guid><description>从数据模型、一致性、访问路径和团队能力四个维度拆解云数据库选型，避免只按技术热度做判断。</description></item><item><title>第 3 篇：Lakehouse 的数据摄入和建模别只盯着批流一体</title><link>https://stdb.top/lakehouse-series/lakehouse-ingestion-and-modeling/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/lakehouse-ingestion-and-modeling/</guid><description>从原始层、清洗层到消费层拆解 lakehouse 数据摄入与建模，避免把所有复杂度都压给一个统一作业。</description></item><item><title>第 3 篇：高可用、备份与容灾的真实成本</title><link>https://stdb.top/cloud-database-series/ha-backup-and-dr/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/ha-backup-and-dr/</guid><description>把高可用、备份与容灾拆成三类不同问题，帮助团队避免在采购和架构设计阶段混淆边界。</description></item><item><title>第 4 篇：Lakehouse 成本问题往往不在存储</title><link>https://stdb.top/lakehouse-series/lakehouse-compute-and-cost/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/lakehouse-compute-and-cost/</guid><description>从扫描量、文件组织、引擎并发和治理边界四方面分析 lakehouse 的成本控制。</description></item><item><title>第 4 篇：性能治理不是只看 CPU</title><link>https://stdb.top/cloud-database-series/performance-governance/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/performance-governance/</guid><description>从 SQL、索引、连接池、热点和流量形态等角度讨论数据库性能治理，而不是只靠升配解决问题。</description></item><item><title>第 5 篇：Lakehouse 真正上线，卡在治理而不是查询引擎</title><link>https://stdb.top/lakehouse-series/lakehouse-governance-and-production/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/lakehouse-series/lakehouse-governance-and-production/</guid><description>从权限、质量、血缘、责任归属和平台边界角度讨论 lakehouse 的生产化治理。</description></item><item><title>第 5 篇：云数据库为什么总是“越用越贵”</title><link>https://stdb.top/cloud-database-series/cost-control/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/cost-control/</guid><description>从资源扩张路径、备份、只读节点、跨区流量和环境治理角度理解云数据库成本控制。</description></item><item><title>第 6 篇：从自建 MySQL 迁移到云数据库的实战路径</title><link>https://stdb.top/cloud-database-series/migration-playbook/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>https://stdb.top/cloud-database-series/migration-playbook/</guid><description>从盘点、验证、同步、校验、灰度切换和回滚预案六个阶段梳理数据库迁移的实战路径。</description></item></channel></rss>