📊 HiddenMerit Daily · Issue 38

Focus on Database Frontiers, Practical Insights for DBAs June 8, 2026 ｜ 5 Selected Global Breaking News

01｜Alibaba Cloud Launches MongoDB 8.3 Domestically: Three “Native” Capabilities for Vector Search, Auto‑Embedding, and Intelligent O&M

On June 1, Alibaba Cloud became the first in China to launch MongoDB 8.3. This version deeply integrates three major AI capabilities – vector search, auto‑embedding, and intelligent O&M – directly into the database engine, moving away from “add‑on” AI solutions and achieving an AI‑Native design philosophy of “no data movement, no capability assembly, simplified architecture.”

Three Native AI Capabilities:

Native Search: Vector and full‑text search are built into the engine layer; a single pipeline completes hybrid search combining “vector + full‑text + scalar,” eliminating the need for applications to switch between multiple systems.
Native Vectorisation: Write‑time auto‑embedding, transparent to applications, zero sync overhead; the entire flow from data write to vector generation is completed within the same database.
Native O&M: Natural language management; AI‑assisted slow query analysis, index recommendations, and parameter tuning, covering all versions.

MongoDB 8.3 also delivers impressive OLTP performance: compared to version 8.0, write throughput increases by 35%, read throughput by 45%, and ACID transaction throughput by 15%, all without any application code changes.

DBA Perspective: Alibaba Cloud MongoDB 8.3’s “three native” design – native search, native vectorisation, native O&M – represents a high‑order form of cloud database AI‑ification. In the past, building a RAG application required DBAs to set up complex ETL pipelines across MongoDB (business data), a vector database (embeddings), and a message queue (sync链路). Now 8.3 completes the entire chain within a single database. The auto‑embedding capability of “write‑time vectorisation” is particularly noteworthy – it fundamentally eliminates data consistency problems, but also means DBAs must redesign the performance baseline and monitoring strategy for the write path.
CTO Perspective: Alibaba Cloud’s domestic launch of MongoDB 8.3 is another major milestone in the “AI‑Native” direction for domestic cloud databases, following Tencent Cloud’s AI‑Native 3.0 upgrade. Moving from “add‑on AI” to “native AI” is a generational shift in database architecture. For CTOs planning data architectures for AI applications, MongoDB 8.3’s design of “a single pipeline for hybrid search” and “zero sync overhead” can significantly reduce the data integration complexity and O&M costs of AI applications.
Investor Perspective: The deep cooperation between Alibaba Cloud and MongoDB, demonstrated by this domestic launch, shows that domestic cloud vendors are seizing market opportunities by introducing world‑leading AI database capabilities. MongoDB’s AI‑Native approach and domestic databases’ AI‑In‑Database approach form a competitive yet cooperative relationship. Investors should pay attention to differences in customer acceptance between these two technology paths in commercial implementation.

02｜Oracle May CSPU Critical Alert: REST Data Services CVSS 10.0 Vulnerability, DBAs Must Act Immediately

In early June, the Cyber Security Agency of Singapore (CSA) and the Taipei Second District Network Center in Taiwan issued urgent alerts regarding multiple vulnerabilities fixed in Oracle’s first monthly Critical Security Patch Update (CSPU) in May. This CSPU fixed 35 vulnerabilities, of which 11 are rated Critical.

Critical Vulnerability Details:

CVE ID	CVSS Score	Affected Component	Description
CVE-2026-46840	10.0	REST Data Services (Backend‑as‑a‑Service)	Unauthenticated attacker can fully compromise the system via HTTPS; attack may impact other connected products
CVE-2026-46817	9.8	E‑Business Suite (Oracle Payments)	Unauthenticated attacker can fully compromise the system via HTTP
CVE-2026-34311	9.8	Hospitality OPERA 5	Unauthenticated attacker can fully compromise the system via HTTP
CVE-2026-46775/CVE-2026-46839	9.9	REST Data Services (Core)	Low‑privilege attacker can fully control REST Data Services
CVE-2026-2332	9.1	REST Data Services (Core/Eclipse Jetty)	Can lead to unauthorised creation, deletion, modification, and reading of critical data
CVE-2026-33557	9.1	Communications Unified Assurance (Apache Kafka)	Can lead to unauthorised creation, deletion, modification, and reading of critical data
CVE-2026-46833	9.0	Database Server (Net Service)	Affects versions 23.4.0 to 23.26.2; can lead to full takeover of Net Service; attack may impact other products

Affected Versions: Oracle REST Data Services 24.2.0 to 26.1.0, Oracle Database Server 23.4.0 to 23.26.2, Oracle E‑Business Suite 12.2.3 to 12.2.15, and others.

DBA Perspective: CVE-2026-46840, with a CVSS 10.0 perfect score, is one of the most severe Oracle vulnerabilities in recent years. REST Data Services serves as the REST API gateway for Oracle databases. The vulnerability in its Backend‑as‑a‑Service component allows an unauthenticated attacker to fully compromise the system via HTTPS – meaning that if an enterprise exposes API interfaces through ORDS, an attacker could directly penetrate the application layer and reach the database core. The affected versions cover most current Oracle 23ai and ORDS deployments. DBAs must immediately assess affected versions and set the CSPU patch to P0 priority. The “scope changed” characteristic of CVE-2026-46833 is also值得警惕 – an attack could extend from Net Service to other affected products, giving this vulnerability a damage radius that may exceed expectations.
CTO Perspective: With Oracle’s shift to a monthly CSPU mechanism, the first patch package already暴露 a CVSS 10.0 vulnerability, indicating that security threat response for traditional commercial databases has become a routine, high‑priority task. The multiple vulnerabilities with scores above 9 in the CSPU are concentrated in REST Data Services and E‑Business Suite, indicating that API gateways and外围 applications are becoming new weak points in database security. CTOs should establish a “monthly security baseline” mechanism and incorporate Oracle patches into CI/CD gates.
Investor Perspective: Oracle’s security maintenance costs continue to rise. In the May CSPU, REST Data Services and E‑Business Suite were the hardest hit areas. This may push enterprise customers to evaluate cloud‑native and open‑source alternatives. The urgent alerts from Singapore’s CSA and the Taiwan region further放大 this signal – regulators have designated the vulnerability as a high‑priority处置对象.

03｜PostgreSQL JDBC Driver Exposes High‑Risk DoS Vulnerability: Malicious SCRAM Authentication Can Crash Client

On June 1, Red Hat released security advisory RHSA-2026:22304, disclosing a high‑risk client‑side denial‑of‑service vulnerability in the PostgreSQL JDBC driver (pgjdbc), tracked as CVE-2026-42198 (CVSS score pending; Red Hat rated it as “Important”).

Core issue: During the SCRAM-SHA-256 authentication process, a malicious PostgreSQL server can send crafted responses causing the client‑side JDBC driver to enter an infinite loop or exhaust memory, ultimately crashing the client application. An attacker can control a malicious PostgreSQL server endpoint to perform a denial‑of‑service attack on Java applications connecting to that server. Affected pgjdbc versions include 42.7.x (before 42.7.5), 42.6.x (before 42.6.3), 42.5.x (before 42.5.6), and others. Red Hat has released updates to fix the issue.

DBA Perspective: The special aspect of CVE-2026-42198 is that the attack surface is not on the database server side, but on the client‑side JDBC driver. Traditional database security focuses on the server side – firewalls, access control, SQL injection defences. But this vulnerability reminds DBAs that client‑side components can also become attack entry points. Java applications using the PostgreSQL JDBC driver face “downstream supply chain risk” – an attacker can attack the client by controlling a malicious database endpoint (e.g., through a phishing‑style data source configuration). DBAs are advised to work with application security teams to identify pgjdbc versions, upgrade to fixed versions, and establish trust verification mechanisms for database connection string sources used by applications.
CTO Perspective: The pgjdbc vulnerability reveals a blind spot in database security – supply chain security of client‑side drivers. For enterprises where the Java technology stack dominates, the potential damage radius of this vulnerability may be underestimated. It is recommended to include database client libraries (JDBC, ODBC, drivers, etc.) in Software Bill of Materials (SBOM) management and establish a regular upgrade mechanism.
Investor Perspective: This vulnerability once again validates the importance of “open‑source software supply chain security.” The attack surface is expanding from the server side to the client side, and from the kernel to drivers. Security companies that can provide deep scanning of open‑source components, dependency analysis, and vulnerability management services will see continued demand growth in enterprise security budgets.

04｜Industrial and Commercial Bank of China Obtains NL2SQL Patent: Major Bank’s AI Application Advances Further

On June 5, the Industrial and Commercial Bank of China (ICBC) was granted a new invention patent titled “Database operation statement generation method, device, computer equipment, and storage medium” (patent application number CN202310728695.4). The patent relates to the field of computer technology and can be applied in the fintech domain.

Patent abstract: It receives natural language information input for operating a database; obtains data structure information from the database; based on the data structure information, determines associated data table information related to the natural language information; converts the natural language information into database language information matching the database operation language environment; and generates a database operation statement based on the associated data table information and the database language information. The patent aims to improve the operational efficiency of database operations.

ICBC has obtained 579 new patent grants this year, with cumulative patent information reaching 22,524 items. Previously, ICBC explicitly proposed the “Digital ICBC (D-ICBC)” strategy in its 2025 annual report, continuously promoting the five major areas of technology finance, green finance, inclusive finance, pension finance, and digital finance.

DBA Perspective: ICBC’s NL2SQL patent is another landmark event in “AI democratising database operations.” When the ability to generate SQL from natural language is deeply integrated into financial‑grade applications, the DBA’s daily work will shift from “responding to business departments’ data requests” to “managing the quality and security boundaries of AI‑generated SQL.” While NL2SQL lowers the barrier to data access, it also introduces new risks – non‑professional users may generate inefficient or even erroneous SQL. DBAs need to establish review mechanisms for AI‑generated SQL, execution plan baseline management, and resource consumption monitoring.

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CTO Perspective: ICBC’s NL2SQL patent is a benchmark event for the integration of “AI + database” in the financial industry. Natural language operation of databases is moving from a “laboratory concept” to “financial‑grade application.” Technology decision‑makers should focus on the accuracy boundaries of NL2SQL in complex business logic (multi‑table joins, aggregations, window functions), and how to开放 AI data access capabilities without impacting production stability.
Investor Perspective: The technology layout of ICBC, as a large state‑owned bank, has industry bellwether significance. The NL2SQL patent indicates that the financial industry is evolving from “AI‑assisted development” to “AI replacing simple data retrieval.” Investors should focus on AI companies with core NL2SQL technology, as well as enterprises providing security auditing and performance optimisation services around NL2SQL.

05｜Sitronix Applies for Database Slow SQL Prediction Patent: AI Enables “Preventative Treatment” for Databases

On June 5, information from the China National Intellectual Property Administration showed that Beijing Sitronix Information Technology Co., Ltd. and Beijing Siyuan Pasi Information Technology Co., Ltd. applied for a patent titled “Database slow SQL prediction analysis method, device, equipment, and medium” (publication number CN122152844A).

Patent abstract: The method实时 acquires SQL statements and associated database environment data during database operation, performs feature extraction to generate feature vectors; based on a pre‑trained slow SQL prediction model (deep learning model), predicts slow SQL, generating a slow SQL probability and predicted execution time; when determined to be a potential slow SQL, determines the root cause category of the slow SQL based on attention weight distribution. The patent relates to the field of deep learning technology, comprehensively applying neural network technologies such as CNN, RNN, and LSTM for feature extraction and融合 analysis.

Sitronix, founded in 1995, is a leading provider of system solutions for the telecommunications industry and was listed on the Shenzhen Stock Exchange in 2017. Its core business covers core business system solutions for the telecom industry, with full‑chain service capabilities.

DBA Perspective: Sitronix’s slow SQL prediction patent represents a paradigm shift in database operations from “passive response” to “active prediction.” Traditional slow SQL治理 is “after‑the‑fact” – a SQL runs slowly, then the DBA looks at the execution plan, adds indexes, or rewrites the SQL. An AI slow SQL prediction model can, before or at the early stage of SQL execution, predict whether it will become a slow query and identify the root cause category. For DBAs, this means that future database operations tools will have “preventative diagnostic” capabilities, and the DBA role will evolve from “firefighter” to “risk predictor.”
CTO Perspective: Sitronix’s patent application reflects the urgent need in the telecommunications industry for intelligent database operations. When AI can predict slow SQL and provide root cause analysis, enterprises can significantly reduce business interruptions caused by performance issues. For technical teams with limited operations personnel, such AI prediction capabilities are a key lever for improving efficiency.
Investor Perspective: Slow SQL prediction is one of the core technologies in the database AIOps field. Sitronix’s patent application indicates that domestic IT service providers are deeply integrating AI into database operations toolchains. Investors should focus on database service providers and operations tool vendors with technical积累 in the AIOps direction.

📅 Recent Database Hot Topics Recap

Date	Event	Core Highlights
June 1	Alibaba Cloud launches MongoDB 8.3 domestically	Native search + native vectorisation + native O&M; moving away from add‑on AI
June 1	Red Hat releases pgjdbc security update	CVE-2026-42198 client‑side DoS vulnerability; malicious SCRAM authentication can cause crashes
June 2	Singapore CSA issues Oracle vulnerability alert	CVE-2026-46840 rated 10.0; severe REST Data Services vulnerability
June 4	Dameng receives multiple institutional investor visits	Detailed explanation of AI4DB and DB4AI dual strategies; revealed global expansion plans
June 5	ICBC obtains NL2SQL patent	Natural language generation of database operation statements; further progress in financial AI
June 5	Sitronix applies for slow SQL prediction patent	AI enables “preventative treatment” for databases; deep learning‑driven proactive operations
June 5	Taipei Second District Network Center issues Oracle vulnerability alert	Multiple CVSS 9.0+ vulnerabilities; REST Data Services hardest hit
Mid‑June	POSETTE: An Event for Postgres 2026	PostgreSQL community annual online event;聚焦 on AI and database integration

📌 Issue Summary

News	Core Keywords	DBA Actions	CTO/Decision‑Maker Focus	Investor Perspective
Alibaba Cloud MongoDB 8.3 domestic launch	Three native capabilities, auto‑embedding, hybrid search	Learn MongoDB 8.3’s auto‑embedding and hybrid search capabilities; assess value of migrating from “add‑on AI” to “native AI”	MongoDB 8.3’s “single pipeline for hybrid search” reduces AI application data integration complexity	Deep cooperation between Alibaba Cloud and MongoDB captures market opportunity; competitive‑cooperative relationship between two AI database paths值得关注
Oracle May CSPU critical alert	CVSS 10.0, REST Data Services takeover, Net Service	Immediately assess Oracle REST Data Services and Database Server versions; set CSPU patch to P0 priority; check ORDS public exposure	Monthly CSPU mechanism makes security response routine; API gateways become new weak point in database security	Rising security maintenance costs push evaluation of cloud‑native and open‑source alternatives
pgjdbc DoS vulnerability	CVE-2026-42198, client‑side crash, malicious SCRAM authentication	Identify pgjdbc versions; upgrade to fixed versions; establish trust verification for database connection string sources	Include database client libraries in SBOM management; establish regular upgrade mechanisms	Open‑source component supply chain security demand continues to grow
ICBC NL2SQL patent	Natural language to SQL, improved database operation efficiency	Establish review mechanisms for AI‑generated SQL, execution plan baseline management	NL2SQL moves from concept to financial‑grade application; need to assess accuracy boundaries	NL2SQL core technology companies and security auditing enterprises benefit
Sitronix slow SQL prediction patent	Active prediction, root cause analysis, deep learning	Transition from “firefighter” to “risk predictor”; focus on AIOps toolchains	AI prediction of slow SQL can significantly reduce business interruptions caused by performance issues	AIOps track gains attention; domestic IT service providers accelerate AI operations tool布局

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