Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models.

The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

As AI evolves from prediction to autonomy, enterprise systems must adapt—meeting new demands in data retrieval, caching, ...

Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

On the morning of August 21, Dameng Data's Vice General Manager, Fu Xin, delivered a keynote speech titled "Intelligent Multi ...

The proliferation of large language models and generative AI has created fertile ground for vector database technologies to flourish.

This approach features a centralized database linked to other data stores with a common data model that carries information from one point to another, without the need to rewrite code.

Data modeling flexibility: Because they are schema-less, they are ideal for various types of data formats, such as document stores, key-value stores, and graph databases.

At Archive of Our Own, a fan fiction database with more than 11 million stories, writers have increasingly pressured the site to ban data-scraping and A.I.-generated stories.