MongoDB Atlas vs. Zilliz Cloud
Compare MongoDB Atlas 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.
MongoDB Atlas vs. Zilliz Cloud on Scalability
Yes. Atlas introduced search nodes, providing dedicated infrastructure for Atlas search and vector search workloads.
Yes.
Yes. At the component level (which provides more fine-grained scalability)
Yes. Atlas can dynamically balance the data between shards via range migrations.
Dynamic segment placement
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.
MongoDB Atlas 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.
Furthermore, differences in insert rate, query rate, and underlying hardware may result in different application needs, making overall system tunability a mandatory feature for vector databases.
Yes - Pre-filtering using an MQL match experssion that compares an indexed field with boolean, number, or string.
Yes, Hybrid sparse and dense search, hybrid keyword and vector search, hybrid vector search and scalar filtering, multimodal search
No. MongoDB organizes data into databases and collections, but it does not have a hierarchical structure like sub-collections within collections.
Yes.
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.
MongoDB (Atlas Vector Search)
Atlas has support for vector embeddings that are less than or equal to 2048 dimensions.
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.
MongoDB Atlas 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:
- Scalability and tunability
- Multi-tenancy and data isolation
- A complete suite of APIs
- An intuitive user interface/administrative console
Add on to Atlas
C#, Java, Node, Pymango
Python, Java, JavaScript, Go, C++, and Node.js SDKs Fully supported
MongoDB Atlas vs. Zilliz Cloud: what’s right for me?
MongoDB (Atlas Vector Search)
Altas is a managed cloud database based on MongoDB document database.
SaaS
Zilliz Cloud
Zilliz Cloud is a fully managed vector database powered by the open-source Milvus vector database.
SaaS
The Definitive Guide to Choosing a Vector Database
Overwhelmed by all the options? Learn key features to look for & how to evaluate with your own data. Choose with confidence.