Pinecone vs Zilliz Cloud

Pinecone vs. Zilliz Cloud

Compare Pinecone 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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Pinecone vs. Zilliz Cloud on Scalability

PineconeZilliz Cloud

Separation of storage and compute

Yes, for the Serverless tier.

Yes.

Separation of query and insertions

Yes, for the Serverless tier.

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

Multi-replication

❌

Dynamic segment placement vs. static data sharding

Static sharding

Dynamic segment placement

Cloud-native

❌

Billion-scale vector support

❌

Pinecone

Pinecone supports the separation of compute and storage with their Serveless Tier.

For its POD-based clusters, Pinecone employs static sharding, which requires users to manually reshard data when scaling out the cluster.

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.

Pinecone vs. Zilliz Cloud on Functionality

PineconeZilliz Cloud

Role-based Access Control (RBAC)

Yes, with limited roles (only Org Owner & members are supported)

❌

Disk Index support

Available with the Pinecone S1 solution only

❌

Hybrid Search (ie Scalar filtering)

Yes. Sparse & Dense Vectors and 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. Users cans organizes data into namespaces and should aware that there are a limited number of namespaces available. Please consult with Pinecone on the limitations.

Yes.

Index type supported

Closed source Index (proprietary)

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

❌

Pinecone

RBAC is not enough for large organizations. Storage optimized (S1 ) has some performance challenges and can only get 10-50 QPS. The number of namespaces is limited and users should be careful when using metadata filtering as a way around this limitation as it will have a big impact on performance. Furthermore, data isolation is not available with this approach.

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.