Chroma vs Zilliz Cloud

Chroma vs. Zilliz Cloud

Compare Chroma vs. Zilliz Cloud by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.

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Chroma vs. Zilliz Cloud on Scalability

ChromaZilliz Cloud

Separation of storage and compute

❌

Yes.

Separation of query and insertions

No. Can not scale beyond single node.

Yes. At the component level (which provides more fine-grained scalability)

Multi-replication

❌

Dynamic segment placement vs. static data sharding

No distributed data replacement

Dynamic segment placement

Cloud-native

❌

Billion-scale vector support

❌

Chroma scalability

Without any distributed data replacement, Chroma is not able to scale beyond a single node

Zilliz Cloud

Zilliz Cloud is a managed vector database service powered by Milvus. Its cloud-native architecture dynamically scales to 10B+ vectors, maintaining high performance and cost-efficiency without the need for new clusters or data sharding.

Chroma vs. Zilliz Cloud on Functionality

Performance is the biggest challenge with vector databases as the number of unstructured data elements stored in a vector database grows into hundreds of millions or billions, and horizontal scaling across multiple nodes becomes paramount.

ChromaZilliz Cloud

Role-based Access Control (RBAC)

❌

Disk Index support

❌

Hybrid Search (ie Scalar filtering)

Yes with scalar filtering

Yes, Hybrid sparse and dense search, hybrid keyword and vector search, hybrid vector search and scalar filtering, multimodal search

Partitions/namespaces/logical groups

❌

Yes.

Index type supported

1 (HNSW)

Cardinal (The world's first AI-based Autoindex mechanism that selects the best search strategy and index for each dataset, eliminating the need for manual tuning.), closed-source.

Multiple in-memory indexes support

❌

Chroma functionality

Chroma uses HNSW algorithm to support kNN search.

Zilliz Cloud

Zilliz Cloud is a managed vector database service powered by Milvus. It uses the world's first AI-based Autoindex mechanism that selects the best search strategy and index for each dataset, eliminating the need for manual tuning. It offers intelligent resource management and tiered storage capabilities to minimize expenses while maintaining superior query speeds, ensuring you never compromise performance.

Chroma vs. Zilliz Cloud on Purpose-built

What’s your vector database for?

A vector database is a fully managed solution for storing, indexing, and searching across a massive dataset of unstructured data that leverages the power of embeddings from machine learning models. A vector database should have the following features: