Just last week, ali released a mission assistant to build a consumer-class smart body as the first important strategy of his year, and the al super-entry contest officially began during the year。
It is worth noting that, also at the launch, when it comes to the capabilities behind mission assistants, the official ali mentioned in particular that the team worked in depth with the major professional databases, thus further enhancing the timeliness and authority of mission assistant outputs。
The importance of data and databases in this age narrative of artificially intelligent rewrite industrial structures is constantly being mentioned, in particular the database that determines data governance capacity and retrieval efficiency, and is being transformed from a data warehouse to an ai reasoning link portal。
The key elements behind the industrialization of these large models, namely accuracy, real-time, cost, are continuously being optimized by the integration of databases with search, vector and rag links, and the database is becoming an engine for industrial intelligence upgrading。
What kind of database does ai need
In 1956, the dartmouth conference at dartmouth college, hanover, united states, became the beginning of artificial intelligence。
Half a century later, artificial intelligence became the core technology of a new wave of technology industries. However, at that time artificial intelligence was already quite different from that of 50 years ago, and today artificial intelligence has evolved into a large model based on big data, big math。
When people are talking about chatgpt, deepseek, big data would not have received such attention without the 2012 hadoop boom, and without big data there would have been no technological paradigm for big models。
It's because of the past
The web-based data base, with a distributed documentation system such as hadop and hdsf, has made it possible to make big data a key element in the field of scientific research, and the database has been born in secret。
The importance of data is self-evident in the age of artificial intelligence in the paradigm of large models, and new demands are coming from databases。
The first is mixed retrieval into a high frequency load。
In the two years that have passed since september 2023, when gpt-4v was released, the large model was no longer at the level of text understanding, and in the wake of the large model, a high demand for mixed data retrieval began to prevail。
In addition to processing structured data, the database will need to process semi-structured or even non-structured data. In addition to the relationship model, the database will need to process semi-structured data by jason or to create semantic indexes for unstructured data, such as vector indexes, graphic indexes, full text indexes, etc。
As a result, the creation of a hybrid search engine based on structured, semi-structured, non-structured data has become a new demand for the database from the ai era, and support for the hybrid search has become a watershed in the ai database。
The second is that it can be traced back to firm ai。
While large models offer unlimited possibilities for intellectualization in all walks of life, they also pose a problem and illusion。
Even the gps-5 published by openai in august 2025, the longfact-concepts hallucination rate still stands at 0. 7 per cent and the factscore hallucination rate at 1 per cent, while if applied in commercial settings, particularly industrial ones, it is often necessary to reach four nine (99. 99 per cent) or even higher accuracy rates。
The smooth application of large models in enterprises requires, on the one hand, a fine-tuning of their own applications and a higher degree of precision in the larger models, and, on the other hand, data traceability, which is like an annotated code for work logs and programmers in the enterprise digital system, which is traceable through data to ensure that the content that is retrieved or generated by each ai is based on real data rather than on illusions。
Faced with such demands as those raised by ai, we can see that data storage, data retrieval, data processing are becoming more and more difficult, that traditional databases are beginning to integrate with vector databases, that rag links are being constructed, and that even that ai reasoning capabilities are being integrated into databases。
02 new opportunities for database ai
Sixty years into its existence, the database has produced five map winners in the field of databases, while, over the past years, foreign databases such as oracle and mysql have virtually monopolized global markets。
The advent of the ai era has created new demands for databases and has become a new age variable for the database industry。
In april 2020, microsoft launched microsoft power platform, at which the microsoft ceo satya nadella stated that each company would become a software company in the face of a digital transition. Microsoft power platform is a low-code platform designed to make every common operator a software developer。
Following this, microsoft power platform evolved into a later microsoft copilot and a low-code platform for digital transformation of aided enterprises such as teams。
In essence, microsoft is doing three things: popularizing data, developing people, and popularizing ai。
Professor zhou haung-young of the chinese university of pedagogical education recently staged the 5th oceanb national student computer system capability competition in 2025“if the data are new powerers, the people who make the databases will have to connect and send it to thousands of households, businesses and businesses, so that the data can be used better, and we will also need to develop a variety of neural networks, using data as an indicator of human experience, to train a variety of artificial brains.”
Back to the first principle, if the data are electric, ai is electrical, and the smart body is electrification。
In such an entirely new technological link, the intelligent will replace the traditional business logic and evolve into a new generation of super-applications and super-entryes, at which point the database becomes directly linked to the intelligent, who will perform complex tasks through in-depth interaction with the core basic data in the database。
The mission of the database is shifting from its previous key core business to a data enabling platform and becoming the engine of the ai era。
What are the opportunities for the chinese database industry in the face of this change
Professor zhou said that “the opportunity in china lies in the fact that the database of the ai era is a true application-driven innovation and in the creation of eco-organization and open-source culture”
The number of clients worldwide has surpassed 4,000, with an average annual increase of over 100 per centThis is one of the emerging chinese database manufacturers。
November 2025, oceanbThis is an official public release of the open source database for the age of aiseekdb。
It is understood that seekdb supports a uniform hybrid search of vectors, full text, specimens and spatial geo-data, deeply integrates ai reasoning and data processing, and is compatible with more than 30 mainstream ai frameworks such as hugging face, langchain and others, and that developers need only three lines of code to quickly build their knowledge base, intelligence and other ai applications。
Seekdb became the national computer system capability contest for university students in 2025 and the 5th oceanb as a primary and light-weight database for aiIt's an official product of the database competition。
The theme of this competition is the key issue of the real bottlenecks in ai。
The people who decide the future of the database
National university computer system capability competition and oceanbIn 2023, the sase database competition was officially included in the national university class a competition approved by the ministry of education and is also considered to be the “national competition” in the field of chinese higher education databases. Since its inception in 2021, the contest has been held for five consecutive sessions, attracting a cumulative number of thousands of students from higher education, forming a complete talent chain from “enabled databases” to “enabled databases”。
National university computer system capability competition 2025 and fifth oceanbThe case database competition attracted 1,223 teams and 2,620 students from universities nationwide。
This competition is based on the "first and final" race. In the initial phase, based on the field project miniob, the players are required to achieve the core modules of the database from zero and an integrated vector search function vector database. In the final stage, open-source a. I. A. Database oceanb was introducedAs a carrier, the theme of the two tracks "inner kernel optimization" and "ai application development" was set:
The former requires a highly enhanced “full-text search + standard filter” hybrid search capability with a recall rate of no less than 0. 95 in the 8 core 16gb unit environment
The latter requires the construction of end-to-end, multi-modular rag systems based on optimised seekdb to output accurate answers within a limited time period and traceable to PDF page numbers or chart sources。
These two tracks correspond to the core claims of “quick” and “stable” in ai, respectively, and refer directly to the key engineering difficulties of “dataxai” integration。
At the scene of last sunday (18 january) at the finals, we saw these young teams, two of which were most impressive to me:
One team is "datab."The team, consisting of three students from the beijing university of transport and research, has only been in school for six months, and even laboratories are not fully familiar with it。
The use of the ai tool is one of the reasons why they were able to quickly take up the topic of the competition, and according to captain taekui, when they read the tens of thousands of lines of seekdb source code, they helped them quickly to understand the different levels of seekdb through a large model; after reading the papers generated some inspiration, a framework design for seekdb was quickly generated through ai and developed for different modules in the architecture design。
The other team, the "scrambling to work" team, was a team of three students from different schools, which, according to captain yang tin li, “as school students were busy and could not find the right teammates, i went to the open-source community to send a job sticker” and, as a result, met zhou zhou zhou of the university of electronics, chengdu college of electronics, and wu jinhua of sion university of electronics, which was the “scrambling team” and finally received good results from the grand saiyan army。
In post-session interviews, when it comes to the value of the database in the ai era, yang tin lian believes that “ai cannot be separated from the data, and that the quality, accessibility efficiency, identity management of the data depend on the bottom of the database and the bottom is stronger and stronger the model”
In 2026, artificial intelligence became a competitive high ground in global science and technology, and intelligence agents are becoming a super-portal to consumer markets, as well as a land-defeating vehicle for the intellectual transformation of enterprises. At a time when databases directly linked to intelligence began to shift from traditional data warehouses to the entrance to the ai reasoning chain。
As the future of the database industry, we have seen this generation of young students naturally have an in-depth understanding and application of ai and have built their own systems and engineering thinking under the grinding of events and topics such as solving engineering problems with the ai raw database。
They are also becoming a reserve for the rise of the chinese database industry。
