Efficient Vector Similarity Search in Recommender Workflows Using Milvus with NVIDIA Merlin

This blog post discusses the integration of NVIDIA Merlin, an open-source framework developed for training end-to-end models to make recommendations at any scale, with Milvus, an efficient vector database created by Zilliz. The integration is beneficial in the item retrieval stage with a highly efficient top-k vector embedding search. The post also highlights how Milvus complements Merlin in recommender systems workflows and provides benchmark results showing impressive speedups with GPU-accelerated Milvus that uses NVIDIA RAFT with the vector embeddings generated by Merlin Models.

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