# 📊 HiddenMerit Daily · Issue 58
> Focus on Database Frontiers, Practical Insights for DBAs
> July 20, 2026 ｜ 5 Selected Global Breaking News
## 01｜CAICT: Domestic Databases Enter Core System “Deep Water,” AI‑Native Leads New Industry Landscape
On July 9, at the 2026 Trustworthy Database Development Conference, CAICT released the “Database Development Research Report (2026).” The report notes that domestic databases have basically completed peripheral system replacement and have officially entered the critical business system breakthrough phase.
Key Data:
- The global database market reached $131.6 billion in 2025 (approximately RMB 894.09 billion).
- The Chinese database market reached $9.49 billion in 2025 (approximately RMB 64.48 billion), and is expected to reach RMB 97.974 billion by 2028, with a CAGR of 13.06%.
- The number of domestic database vendors has shrunk from a peak of 167 to 94, with a clear head‑concentration effect and an intensifying “Matthew effect.”
AI‑Native Becomes the Main Theme: The report points out that database technology is accelerating its evolution toward the AI‑native direction, and the global database industry is entering a new phase of landscape restructuring. The role of databases is upgrading from “underlying support systems” to “core engines enabling intelligent decision‑making and business innovation.” AI agents are becoming a new type of database interaction subject – over 60% of new databases on the Supabase platform are automatically created by AI agents. The database role is evolving from a “back‑end storage tool” to an “AI runtime core workbench and long‑term memory hub.”
- DBA Perspective: The reduction in vendor count from 167 to 94 means the window for technology stack selection is narrowing – DBAs should focus on the technology stacks of leading vendors. With domestic databases entering the “core system breakthrough phase,” DBA skills must upgrade from “basic operations” to “multi‑modal data processing and mixed‑load tuning under AI‑native architectures.” AI agents becoming new database users means DBAs’ focus will shift from “serving human users” to “serving AI agents,” requiring a redesign of permission governance and audit trails.
## 02｜Transwarp Releases GPU‑Native Cognitive Database: 20‑100x Performance Improvement, Entire Database “Moved” to GPU
On July 18, at the 2026 World Artificial Intelligence Conference (WAIC), Transwarp released a preview of its next‑generation GPU‑Native Cognitive Database for AI agents, moving the complete database functionality – SQL analytics, vector search, graph computing, full‑text search – entirely to GPU, achieving the world’s only complete GPU‑native database.
Core Performance Data:
- In TPC‑DS benchmarks: 70x performance improvement over mainstream open‑source databases; 66x over Snowflake and Databricks, with 14x better price‑performance.
- In TPC‑H benchmarks: 28x performance improvement.
- Document parsing performance improvement of 10‑30x, vector index build performance improvement of up to 50x, and retrieval throughput improvement of up to 238x.
Why a GPU‑Native Database is Needed: Transwarp CEO Sun Yuanhao pointed out that the working mode of AI agents has evolved from “question‑and‑answer” to “reasoning loops” – in a single task, an agent may repeatedly call data hundreds of times, and the compute and bandwidth bottlenecks of traditional CPU‑centric databases are rapidly magnified. In traditional architectures, GPUs handle inference while CPUs handle data queries, with data being transferred back and forth over the PCIe bus. A significant amount of time is wasted on “data waiting.” A single CPU has only a few hundred cores and approximately 400GB/s memory bandwidth, while a GPU has tens of thousands of parallel units and several TB/s of video memory bandwidth.
- DBA Perspective: Transwarp moving the complete database to the GPU represents a paradigm revolution at the database architecture level. For DBAs, this means the dimensions of database tuning will expand from “CPU core count, memory allocation, disk I/O” to “GPU video memory management, parallel stream scheduling, and data residency strategies.” Sun Yuanhao’s judgement that “in the next three to five years, computers will shift entirely from a CPU‑centric to a GPU‑centric architecture” means DBAs need to learn the architectural principles and performance tuning methods of GPU databases in advance.
## 03｜Mobile Cloud HaishanDB Passes First Cloud‑Native Database National Standard Test: First in China to Receive Authoritative Certification
On July 13, Mobile Cloud HaishanDB officially passed the GB/T 47343-2026 “Information Technology – Technical Requirements for Cloud‑Native Relational Database Management Systems” national standard compliance test, becoming the first in China to pass this standard.
Significance of the National Standard: This standard, issued by the State Administration for Market Regulation and the National Standardization Administration, is the first cloud‑native national standard in the domestic database industry. It defines two technical reference models – storage‑compute separation and three‑layer pooling – and specifies hard indicators for basic functionality, elastic scheduling, high availability, data security, and self‑service operations.
HaishanDB Capabilities: As China Mobile’s self‑developed database product after ten years of R&D, HaishanDB features high scalability, high performance, high availability, high security, and low cost. It has been deployed in nine industries including government, healthcare, education, telecommunications, and internet, covering 31 provinces nationwide, supporting over 6,000 core business systems in stable operation. In 2025, it received the “Security and Reliability Level I” certification, fully adapting to mainstream domestic chips and operating systems.
- DBA Perspective: The establishment of a cloud‑native database national standard provides DBAs with a “quantifiable” framework for Xinchuang selection. As the first product to pass the test, HaishanDB means DBAs may increasingly encounter this technology stack in operator and government‑enterprise projects, requiring early preparation of cloud‑native architecture knowledge.
## 04｜Weekly Security Vulnerabilities Focus: Metabase RCE (CVSS 9.9), CVE-2026-16228 SQL Injection, and Others Disclosed
Multiple high‑risk security vulnerabilities were disclosed this week:
Metabase Remote Code Execution (CVE-2026-59827, CVSS 9.9) : Affects multiple Metabase versions. The bundled H2 database has an insecure deserialisation issue. Attackers with an authenticated account can execute native H2 queries that return serialised Java objects. Metabase deserialises these without type checking, allowing arbitrary code execution on the server. CVE-2026-59826 (CVSS 9.1) : Administrators can bypass validation by registering a crafted H2 connection and run arbitrary Java code. Immediate upgrade to versions 1.61.1.4, 1.60.6.3, 1.59.12, or 1.58.15 and above is recommended.
SourceCodester Class and Exam Timetabling System SQL Injection (CVE-2026-16228) : Affects version 1.0. The /edit_schoolyr.php endpoint does not use parameterised queries for the id parameter, allowing remote unauthenticated attackers to read or modify the database. No official fix has been released. It is recommended to deploy WAF rules to intercept SQL injection attempts on this endpoint.
- DBA Perspective: The CVSS 9.9 rating of the Metabase H2 database deserialisation vulnerability means a low exploit barrier and high impact. DBAs using Metabase should immediately check versions and upgrade. CVE-2026-16228 once again confirms that SQL injection at the enterprise application layer is still frequent. DBAs should work with security teams to regularly audit application‑layer components with “database read/write privileges.” Metabase’s default use of H2 as an example database leaves many instances exposed by default, reminding DBAs to disable or replace default example components in production environments.
## 05｜2026 Trustworthy Database Conference: OceanBase, Dameng, Kingware and Other Leading Vendors Present
On July 9, the 2026 Trustworthy Database Development Conference, themed “Strengthening Foundations, Intelligent Integration, and Innovation,” was held in Beijing. CAICT Vice President Wei Liang released the “Database Development Research Report (2026),” noting that domestic databases are moving from “peripheral replacement” to “core breakthrough.”
Leading Vendor Developments:
- OceanBase: Together with CAICT and Shenzhou Information, Neusoft Group, Hundsun Technologies, and Huaxin Yongdao, launched the Critical Industry “AI Database” Initiative, focusing on critical business workloads and accelerating AI innovation.
- Dameng: Attended the conference and shared perspectives on database evolution directions and industry practices in the AI era.
- CETC Kingware: Attended the conference and shared implementation practices for AI‑native databases. Previously, it reached a strategic cooperation with Hygon Information and Kylin Software, forming a “chip + operating system + database” iron triangle.
- China Mobile: Panyu Database is evolving from AI‑driven to AI‑native, with implementations in scenarios such as multi‑modal knowledge retrieval and agent memory collaboration.
The conference concurrently released Trustworthy Database test results, with 21 products from 16 enterprises passing 30 tests. Eight new Trustworthy Database standards were added, focusing on core system applications and digital‑intelligent integration.
- DBA Perspective: The concentrated presence of leading vendors at the Trustworthy Database Conference validates the large‑scale maturity of domestic databases in critical industries such as finance, telecommunications, and government. The launch of the initiative means “AI databases” are moving from concept to large‑scale government and enterprise implementation.
## 📚 SQL Little Knowledge Point
This Issue’s Knowledge Point: What is a “GPU‑Native Database”?
A “GPU‑Native Database” refers to a database where the complete functionality – including SQL analytics, vector search, graph computing, full‑text search – is fully migrated to run on the GPU, rather than merely offloading a few operators to the GPU as a coprocessor.
Traditional Architecture vs. GPU‑Native Architecture:
| Dimension | Traditional CPU Database | GPU‑Native Database |
|-----------|------------------------|---------------------|
| Compute Cores | CPU (hundreds of cores) | GPU (tens of thousands of parallel units) |
| Memory Bandwidth | ~400GB/s | ~several TB/s |
| Data Path | PCIe transfer between CPU and GPU | Data directly resides in GPU video memory |
| AI Agent Support | Data transfer becomes bottleneck | Query results feed directly into inference |
Transwarp’s Implementation: Transwarp’s GPU‑Native Cognitive Database achieved 66x performance improvement and 14x better price‑performance over Snowflake and Databricks in TPC‑DS benchmarks. Sun Yuanhao noted: “If you only offload a few operators to the GPU as a coprocessor, the bottleneck is still data transfer, and the speedup is only 1.5x, which is not economical. Only by fully migrating the complete functionality can you achieve a speedup starting at 20x.”
Significance for DBAs: A GPU‑native database means the dimensions of DBA tuning will expand from CPU cores, memory allocation, and disk I/O to GPU video memory management, parallel stream scheduling, and data residency strategies. Sun Yuanhao’s judgement that “in the next three to five years, computers will shift entirely from CPU‑centric to GPU‑centric” means DBAs need to build GPU database architecture knowledge in advance.
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