G2

andrew c.

NLP Engineer

Enterprise (> 1000 emp.)

11/5/2025

"Efficient Zilliz for Entity Alignment, Disambiguation, and RAG Recall in Knowledge Graphs"

5/5

What do you like best about Zilliz?

I love how Zilliz excels at scalability and high-performance vector search, making it incredibly efficient for handling massive datasets in AI-driven tasks. In my experience, its hybrid retrieval capabilities—combining vector embeddings with knowledge graph integrations—stand out, especially for complex queries involving semantic understanding. It's easy to integrate with tools like LangChain and OpenAI embeddings, and the cloud-native features in Zilliz Cloud simplify management without sacrificing speed or accuracy. Review collected by and hosted on G2.com.

What do you dislike about Zilliz?

For self-hosted Milvus setups, the configuration might feel a bit involved compared to fully managed options, but Zilliz Cloud largely resolves that with its user-friendly UI and elastic scaling. Review collected by and hosted on G2.com.

What problems is Zilliz solving and how is that benefiting you?

Zilliz is tackling challenges in entity alignment and disambiguation within my knowledge graph project by leveraging vector embeddings and graph-based retrieval to link and resolve entities across diverse datasets, reducing ambiguities (like distinguishing similar terms in different contexts) and enabling precise multi-hop reasoning. This has streamlined entity matching, cutting down on manual corrections and improving overall graph accuracy. In the recall step of my RAG pipeline, it enhances retrieval of relevant documents through hybrid searches (vector similarity plus relational structures), minimizing hallucinations in LLM outputs and providing more complete, contextually rich responses. Overall, it's saved me significant time on data processing, boosted the reliability of my AI applications, and allowed for handling larger-scale data without performance drops—ultimately making my projects more efficient and effective. Review collected by and hosted on G2.com.