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Lantern vs Qdrant

A side-by-side comparison of Lantern and Qdrant, two Vector DB tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Lantern

Vector DB

Open-source Postgres vector database for AI apps.

View Lantern

Qdrant

Vector DB

Open-source, Rust-based vector DB. Fast, predictable, self-hostable.

View Qdrant

At a glance

Feature comparison of Lantern and Qdrant
AttributeLanternQdrant
CategoryVector DBVector DB
PricingFREEMIUMFREEMIUM
LicenseOpen coreOpen core
DeploymentHybridHybrid
Platforms (differs)API, Linux, macOSAPI
Model supportModel-agnosticModel-agnostic
Vendor (differs)LanternQdrant

The honest brief

Lantern

Adds production vector search inside Postgres itself — HNSW indexing and hybrid BM25 search with no separate vector store.

  • Lives inside the Postgres you already run
  • Open-source, self-host or managed cloud
  • HNSW plus hybrid BM25 search
  • Built-in embedding generation
  • Tied to the Postgres ecosystem
  • Smaller community than pgvector
  • Managed cloud tier still maturing

Qdrant

Rust single-binary you can self-host, with payload filtering strong enough that teams pick it for metadata-heavy search.

  • Open source, written in Rust
  • Self-host or managed cloud
  • Strong payload/metadata filtering
  • Predictable latency at scale
  • More ops than fully-managed rivals
  • Smaller ecosystem than Pinecone
  • Advanced features lean on managed cloud