Comparisons
Zilliz Cloud vs KDB.AI

Zilliz Cloud vs. KDB.AI

Compare Zilliz Cloud vs. KDB.AI 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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Zilliz Cloud vs. KDB.AI on Scalability

Zilliz CloudKDB.AI

Separation of storage and compute

Yes.

❌

Separation of query and insertions

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

Yes.

Multi-replication

❌

Dynamic segment placement vs. static data sharding

Dynamic segment placement

Neither.

Cloud-native

❌

Billion-scale vector support

❌

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.

KDB.AI

KDB.AI is a scalable vector database.

Zilliz Cloud vs. KDB.AI on Functionality

Zilliz CloudKDB.AI

Role-based Access Control (RBAC)

❌

Disk Index support

❌

Yes (qFlat and qHNSW)

Hybrid Search (ie Scalar filtering)

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

Yes. Hybrid Sparse & Dense Search

Partitions/namespaces/logical groups

Yes.

❌

Index type supported

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.

Flat, qFlat, IVF, IVFPQ, HNSW, and qHNSW.

Multiple in-memory indexes support

❌

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.

KDB.AI

Built by KX, a database provider known for time-series data management, KDB.AI enables developers to bring temporal and semantic context and relevancy to their applications. It supports various search types, including vector similarity search, hybrid sparse and vector search, and Non-Transformed TSS, a similarity search algorithm specific for time series data. It uses Cosine Similarity, Inner Product, and L2 Distance (Euclidean) for similarity metrics.

Zilliz Cloud vs. KDB.AI on Purpose-built

Zilliz CloudKDB.AI

Purpose-built for Vectors

❌

Yes.

Tunable consistency

❌

Support for both stream and batch of vector data

❌

Binary Vector support

❌

Multi-language SDK

Python, Java, JavaScript, Go, C++, and Node.js SDKs Fully supported

Python

Database rollback

✔️

❌

Zilliz Cloud vs. KDB.AI: what’s right for me?

Zilliz Cloud

Zilliz Cloud is a fully managed vector database powered by the open-source Milvus vector database.

SaaS

KDB.AI

KDB.AI is a powerful knowledge-based vector database and search engine that allows you to build scalable, reliable AI applications using real-time data.

Proprietary license