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On October 30, Jincang (DBKing) released the KES AI database in Beijing, embedding the semantic layer, vector and graph computing, and permission auditing into the database kernel, so that enterprise data can support AI applications without leaving the database. The company claims that under the condition of 100 million 768-dimensional vectors and a 98% recall rate, the disk-based indexing algorithm reduces peak memory overhead by 95.4% and query latency by 80% compared with the industry. The product also comes with KES MCP, Agent Skills, NL2SQL agents and operations agents, and supports migration and upgrade of existing databases.
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- Source:36Kr · AI
Reports and discussion timeline
Browse reports and discussion by time. Their evidence levels remain distinct.
Nov 3
Titanium Media · AGI
In the year when AI databases were released in droves, what did products such as the Electric Power Golden Warehouse KES AI upgrade?
At the end of October, Electric Power Golden Warehouse released the KES AI database, incorporating semantic construction, computational reasoning, and native data security control into the database kernel, emphasizing that AI applications can be supported without data leaving the database. Alibaba Cloud PolarDB launched capabilities such as the AI data lakehouse (Lakebase) in January this year and launched PolarDB Agentic Database in July, while OceanBase packaged its AI direction into the OceanBase AI Database product portfolio in June. IDC data shows that the market size of China's AI data infrastructure in 2025 is approximately 14.9 billion US dollars, and will reach 73.8 billion US dollars by 2030.
Oct 31
36Kr · AI
Kingbase (CESI) Releases KES AI Database, Embedding AI Capabilities into the Database Kernel
On October 30, Kingbase (CESI) released the KES AI database in Beijing, incorporating the semantic layer, vector and graph computing, and permission auditing into the database kernel, enabling enterprises to support AI applications without their data leaving the database. The company claims that under the conditions of 100 million 768-dimensional vectors and a 98% recall rate, its disk-based indexing algorithm reduces peak memory overhead by 95.4% and query latency by 80% compared with the industry. The product also comes with KES MCP, Agent Skills, NL2SQL agents, and operations agents, and supports migration and upgrades from existing databases.