数据库周报

AI落地案例丨广西桂物机电集团：告别繁琐找数，自然语言解锁经营洞察

从AI驱动的数据治理，到自然语言问数，再到 Agent 深度分析，达梦数据的 AI 能力正沿着“数据治理-智能分析-业务决策”的链路，在广西桂物机电集团的真实业务里落地生根。以达梦多模态智能数据库底座为支撑，这些 AI 能力得以深度融入业务现场。

PostgreSQL 10 月技术工作坊：执行计划稳定性与 pg_plan_advice

Robert Haas 公布 10 月工作坊主题，讨论 pg_plan_advice、执行计划稳定性以及用户对规划器的控制，并提供报名入口。

FireTV 如何通过并行查询和垂直分区优化 DynamoDB

AWS 分享 FireTV 观看进度系统的数据模型改造：通过并行查询与垂直分区突破单条记录大小限制。案例报告写入成本下降 97%，平均读取延迟为个位数毫秒、P99 低于 50 毫秒；这些数值来自该业务场景。

校企合作 产教融合 | 瀚高股份与华东师范大学签署战略合作协议，携手共建“AI数据库开源联合实验室”

瀚高股份与华东师范大学签署战略合作协议，携手共建“AI数据库开源联合实验室”

Elasticsearch 8.19.22

Downloads: https://elastic.co/downloads/elasticsearch Release notes: https://www.elastic.co/guide/en/elasticsearch/reference/8.19/release-notes-8.19.22.html

PostgreSQL 故障切换后，archive_mode 如何影响 pgBackRest 备份？

案例中备库在 archive_mode=off 时被提升为主库，随后尝试从下游备库备份仍遇到归档检查失败。作者建议通过重启或受控切换恢复受支持配置，而不是删除 pgBackRest 的检查代码。

PostgreSQL 入门：使用 Docker 启动数据库

Grant Fritchey 的 PostgreSQL 入门系列从容器环境开始，介绍如何启动实例并创建数据库及其对象，适合学习和实验。

Oracle MySQL 官方博客MySQL行业动态

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MySQL 第 6 次公开讨论与 11 月贡献者峰会开放参与

MySQL 社区邀请用户、DBA、开发者和贡献者参与技术讨论、反馈问题并交流后续发展方向。

Azure SQL 解释 DevOps 审计 API 的迁移行为

微软说明旧的 isDevopsAuditEnabled 配置为何在部分服务器上表现不同，并指出独立的 devOpsAuditingSettings 资源是当前受支持的配置方式。

TideSQL 5 and MariaDB: the Tides Are Moving Fast

A few months ago, I wrote about my first experiments with TideSQL , the MariaDB storage engine powered by TidesDB . At that time, getting started meant building the TidesDB library, adding the TideSQL sources to the MariaDB source tree, compiling everything, installing the plugin and finally playing with: It worked, and I liked what I saw. … Continue reading \"TideSQL 5 and MariaDB: the Tides Are Moving Fast\" TideSQL 5 and MariaDB: the Tides Are Moving Fast appeared first on MariaDB.org

Oracle 社区发布 Joel Kallman Day 2026 活动公告

Oracle-Base 介绍社区在同一天集中分享技术内容的年度活动，并回顾该活动自 2021 年起采用 Joel Kallman Day 名称的背景。

PostgreSQL安全动态

It’s been a month since I published the first part of this research, and interest from the Postgres community has been higher than I expected. Most vendors I contacted were shy to respond, so the Databricks team’s blog post Collaboration makes us all stronger was one of the first examples of a vendor publicly sharing their side of the story. In the past four weeks, I spoke with managers of managed Postgres services, security engineers, and red teamers who look for new threats in the services they offer. Here’s what I learned from those conversations: None of them had monitoring in place for the shared-buffer-based superuser backdoor technique I described in my first article. Risks from extensions are just as serious as having a zero-day in PostgreSQL core, but no one seems to be focusing o

Christophe Pettus: All Your GUCs in a Row: max_pred_locks_per_transaction

max_pred_locks_per_transaction has the naming problem of max_locks_per_transaction, and then one of its own. Like its namesake, it is a table size quoted per backend slot, not a limit on any transaction. Unlike its namesake, most of what its table holds at any given moment belongs to transactions…

SQL Server 2025 锁优化：减少锁持有与阻塞，也有适用边界

文章解释事务 ID 锁如何帮助更早释放行锁和页锁，以及开启 RCSI 时 Lock After Qualification 的行为，讨论这些变化对并发事务的影响。

PostgreSQL 官方新闻PostgreSQL版本发布

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PgBouncer 1.26.0 发布，修复三项拒绝服务漏洞

修复 CVE-2026-19888、CVE-2026-6668 和 CVE-2026-6669，涉及 SCRAM 认证与数据包缓冲区处理。新增 pool_idle_timeout，支持按用户和数据库配置 query_wait_timeout，并移除已弃用的 -R 在线重启功能。

Intuitive risk investigation with Amazon Neptune and Linkurious Enterprise

One of the challenges organizations face when adopting graph technology for risk investigation and analysis is the relative scarcity of query examples and learning resources compared to SQL. Although graph query languages like openCypher and Gremlin are powerful, finding practical examples and patterns to reference can be more difficult than with traditional database technologies. This means that even after the initial technical setup is done, teams might need additional support to derive full value from their graph data. Common use cases include fraud investigation, money laundering detection, and supply chain risk analysis. This is where Amazon Neptune combines with the user-friendly, flexible, and scalable graph visualization and analytics solutions from Linkurious. Developed to democra

EDB 回顾 2026 首尔 Postgres AI 峰会合作伙伴活动

EDB 回顾韩国合作伙伴在首尔峰会中的参与，介绍其围绕事务数据库、分析与 AI 工作负载发展的合作生态。

Christophe Pettus: The Shadow Knows

ClickHouse released WalShadow last week, and it does something very… brave: it replicates PostgreSQL into ClickHouse without using logical decoding at all. It reads the physical WAL stream, the same bytes a streaming replica gets, decodes heap records itself, and writes ClickHouse-native blocks. …

数兴三晋 智筑新程 | 2026 山西信息技术应用创新峰会暨 GBASE 数据库中华行圆满收官

6个智能运维Agent，提前祝您中秋团圆！

DBA 的时间，应该花在刀刃上。达梦数据库一体机搭载的智能运维监控平台 SmartPAI，以六大专家 Agent 协同，用一行指令让全平台巡检自动落地。

AI落地 实数融合丨瀚高股份亮相2026政企数智化创新发展交流会

瀚高股份亮相2026政企数智化创新发展交流会

石化领域首家！MongoDB国产化替代落地

PostgreSQL备份复制：logical · replication

A long time ago I ran a write-heavy system on a hub and a handful of workers. Each worker took a share of the application traffic and wrote events locally. The hub owned the reference data (customers, plans, prices), pushed it down to the workers, and pulled every worker’s events back up to compute the invoices. The plumbing was Londiste and PgQ: triggers on every table, a queue per node, a ticker, and a Python daemon per hop. It worked, and it was a lot of moving parts to explain to anyone new. Postgres 10 shipped logical replication in 2017, and 19 is the tenth release that has it. Every release since Postgres 10 has taken a piece of that plumbing and made it a line of SQL. This is the first article in a series about Postgres logical replication use-cases, and about how the feature

Release v26.9.2.8-stable

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