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Graph databases are exploding, thanks to the AI boom - here's why
Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.
More recently, there has been a boom in the use of artificial intelligence(AI), both in backend systems and through the rise of generative technologies, creating an insatiable demand for databases that can handle and process super-sophisticated workloads. Spending on these technologies will have a five-year compounded annual growth rate of more than 26%, according to estimates published by tech analyst Gartner at the end of 2024. Graph environments can be applied to functions, such as real-time analytics, fraud analytics, retail, and logistics, said Shalvi Singh, founder of Healthengine.us, and senior product manager at Amazon AI: "Knowledge graphs are aiding large language models by offering ample context for structured reasoning and by enabling contextual understanding."
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