MongoDB Atlas vs. LanceDB
Compare MongoDB Atlas vs. LanceDB 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. LanceDB on Scalability
Yes. Atlas introduced search nodes, providing dedicated infrastructure for Atlas search and vector search workloads.
Yes.
Yes. Atlas can dynamically balance the data between shards via range migrations.
No (static data sharding coming soon)
LanceDB
LanceDB is an open-source vector database that's designed to store, manage, query and retrieve embeddings on multi-modal data. LanceDB and its underlying data format, Lance, are built to scale to really large amounts of data (hundreds of terabytes, 200M+ vectors).
MongoDB Atlas vs. LanceDB 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, vector search & keyword search
No. MongoDB organizes data into databases and collections, but it does not have a hierarchical structure like sub-collections within collections.
HNSW
IVF-PQ, HNSW
(LanceDB adopts a disk-based indexing philosophy.)
MongoDB (Atlas Vector Search)
Atlas has support for vector embeddings that are less than or equal to 2048 dimensions.
MongoDB Atlas vs. LanceDB 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, Javascript/Typescript, and Rust
MongoDB Atlas vs. LanceDB: what’s right for me?
MongoDB (Atlas Vector Search)
Altas is a managed cloud database based on MongoDB document database.
SaaS
LanceDB
LanceDB is an open-source vector database that's designed to store, manage, query and retrieve embeddings on multi-modal data. It also provides a SaaS solution called LanceDB Cloud that runs serverless in the cloud.
Apache 2.0
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.