Documentation ↗Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
Marqo handles embedding generation and vector search together, so you send text or images and it does the rest — no separate embedding step.
| Category | Vector database |
| Type | Vector search engine |
| License | Apache-2.0 |
| Runs locally | Yes |
| Built with | Python |
| Skill level | Beginner |
| Best for | teams who do not want to manage embeddings |
Other open-source vector database tools worth comparing:
QdrantFast Rust-based vector search
WeaviateVector DB with built-in modules
MilvusBillion-scale vector database
ChromaThe simplest embedding DB for prototyping
pgvectorVector search inside PostgreSQL
LanceDBServerless vector DB for AI
FAISSThe reference library for similarity search
VespaBig-scale hybrid search and ranking platform
pgvectorscaleMake pgvector fast at scale
USearchTiny, extremely fast vector indexMarqo is free and open-source (Apache-2.0 license), so you can use, self-host and modify it at no cost.
Yes. Marqo is designed to run on your own machine or server, keeping your data private.
Popular open-source alternatives include Qdrant, Weaviate, Milvus. See the comparisons above to choose.
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