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Zilliz

Managed vector database and vector lakebase for AI applications

Overview

What Zilliz does

Zilliz is the company behind Milvus, the world's most widely-adopted open-source vector database. Zilliz Cloud is a fully managed service that handles the operational complexity of running vector search infrastructure, enabling organizations to easily manage, search, and retain vectors at any scale without managing compute. Milvus, the underlying technology, is distributed under the Apache License 2.0 and part of the LF AI & Data Foundation, supporting billions of vectors through its distributed architecture that separates storage and compute. The platform handles high-dimensional vector embeddings with advanced indexing for efficient similarity search, making it ideal for building RAG applications, semantic search, multimodal search, and recommendation systems. Zilliz Cloud offers a fully managed alternative to self-hosting while maintaining compatibility with the open-source Milvus project.

What people use it for

  • Build retrieval-augmented generation (RAG) systems
  • Implement semantic search over documents
  • Create multimodal search with text and images
  • Power recommendation engines with vector similarity
  • Enable similarity search on user embeddings

The honest half

Where it falls short

Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Zilliz.

  • Pricing structure not publicly disclosed, requires sales contact
  • Operational complexity for self-hosted Milvus deployments
  • Learning curve for those unfamiliar with vector databases
  • Limited built-in analytics compared to some alternatives

Cross-shopped

What people choose instead of Zilliz

Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.

  • Zilliz logo
    Zilliz
    vs
    Pinecone logo
    Pinecone

    Pinecone: Managed vector database with simpler pricing model and API

  • Zilliz logo
    Zilliz
    vs
    Weaviate logo
    Weaviate

    Weaviate: Open-source vector database with hybrid search capabilities

  • Zilliz logo
    Zilliz
    vs
    Qdrant logo
    Qdrant

    Qdrant: Vector database optimized for semantic search and recommendations

Capabilities

Features

  • Vector indexing

    Efficient indexing for billion-scale vectors

  • Distributed architecture

    Separated storage and compute for scaling

  • SQL interface

    Query vectors using SQL with new syntax

  • Tensor support

    Handle high-dimensional tensor operations

  • Real-time search

    Low-latency similarity search operations

  • Cloud-native

    Serverless vector database with managed scaling

  • Open-source compatible

    Drop-in replacement for self-hosted Milvus

Answered, with sources

Questions people ask

Each answer names the page it came from, so you can check it rather than take our word for it.

What is the difference between Milvus and Zilliz Cloud?

Milvus is the open-source vector database that you can self-host. Zilliz Cloud is the fully managed service built on Milvus that removes operational overhead and handles scaling automatically.

Source
How many vectors can Zilliz handle?

Milvus and Zilliz Cloud can store and search billions of vectors through their distributed architecture that separates storage and compute layers.

Source
Is Milvus open-source?

Yes, Milvus is open-source under the Apache License 2.0 and is part of the LF AI & Data Foundation.

Source
What pricing does Zilliz Cloud offer?

Zilliz Cloud pricing is not publicly listed and requires contacting their team to discuss your specific scale and use case requirements.

Source

Behind it

Who makes Zilliz

Company
Zilliz
Based in
Redwood City, CA
Founders
Charles Xie

Timeline

Zilliz over time

  1. Milestone2023-11-01

    Milvus 3.0 released with lake-native data access

    Source
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Softwr does not host reviews and shows no star rating for Zilliz, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.

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