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Vector search, or vectorization, especially in the wake of generative AI proliferation, is seen as a key capability by database vendors as it can reduce the time required to train AI models by cutting down the need to structure data — a practice prevalent with current search technologies. In contrast, vector searches can read the required or necessary property attribute of a data point that is being queried.
This means that these developers can continue to write code in the language that they are familiar with, thereby reducing the time required to develop AI-based applications which are in demand presently, it added.
Further, the new API, which can be accessed via DataStax’s open source API gateway, dubbed Stargate, will also provide compatibility with Mongoose — one of the most popular open source object data modeling library for MongoDB.
In October last year, DataStax launched the second version of its open-source data API gateway, dubbed Stargate V2, just months after making its managed Astra Streaming service generally available.
In June this year, the company partnered with Google to bring vector search to Astra DB.
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