Marqo

https://www.marqo.ai

End-to-end multimodal (text + image) vector search via single API. Handles embedding generation internally. Ecommerce personalization with proprietary models.

At a glance

Type
Multimodal vector via single API
Tier
T2
Created
2022
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Pay-per-use
Funding
$18M Series A · 2024-02

Taxonomy

storage
vector
retrieval
similarity
persistence
long-term
update
overwrite
unit
chunk
governance
inspectable
conflict
overwrite

When to use

Optimised for: low-latency similarity search + scale

Anti-fit: not for relational / graph-heavy queries (vector-first by design)

Pros & cons

Pros

Tightly integrates embedding generation with vector search — no separate embedding pipeline needed.

Cons

Smaller community than mainstream vector DBs; less flexibility on embedding model choice.

Claims & capabilities

LangChain vector store integration.

Technical surface

API surface
REST, SDK: Python, JS
Backend storage
custom (Vespa-backed)
Deployment
Both
Embedding model
multiple supported
Multi-tenancy
namespace
MCP
no first-party MCP adapter published as of 2026-05; community connectors may exist.
A2A
no Google A2A (Agent2Agent) integration documented as of 2026-05.
OpenTelemetry
no first-party OpenTelemetry exporter documented; standard logs/metrics typically available.

Similar systems

Other vector-database infrastructure in the catalog, ranked by inbound references.

  • Qdrant T1

    Distribution-Based Score Fusion + RRF. Sparse vectors native; filtering via ANN graph modification.

  • pgvector T1

    Stores embeddings alongside relational + full-text data. HNSW + IVFFlat ANN indexes. Used as agent conversation memory via LangChain + MCP. Foundation of Supabase AI and many self-hosted RAG stacks.

  • Pinecone T1

    Managed vector DB. Cascading sparse + dense + rerank pipeline; pinecone-rerank-v0 .

  • Chroma T1

    Limited native hybrid (users build RRF custom). Fast Rust core (v2.5).

  • LanceDB T1

    Embedded vector DB (Arrow columnar). RRF reranker. Petabyte-scale on disk.

  • MongoDB Atlas Vector Search T1

    Agent memory store for both short-term (document) and long-term (vector). LangGraph checkpointer for stateful agents. Vector search extended to Community Edition (Sept 2025).

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.