Qdrant vs Weaviate

Qdrant vs Weaviate: side-by-side comparison of two vector-database infrastructure systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.

Qdrant · Weaviate

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Cost & capability

QdrantWeaviate
Cost tierfreefree
$/Mtok input00
$/Mtok output00

Where they differ (13)

Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.

QdrantWeaviate
TypeVector DB + DBSF + RRFHybrid vector DB + learned ranking
Created2020-052016-03
Latest releasev1.19.2 (2026-10-05)v1.40.2 (2026-10-21)
LicenseApache-2.0BSD-3-Clause
GitHubqdrant/qdrant — ~34.9k stars, last commit 2026-10weaviate/weaviate — ~16.8k stars, last commit 2026-10
PricingFree tier forever (single node, 1 GB RAM / 4 GB disk); Standard usage-based hourly billing; Premium has minimum spend; Hybrid/Private Cloud via salesFree cluster $0 (100k objects, 1 GB RAM, 10 GB disk); Flex pay-as-you-go from $45/mo; Premium prepaid via sales; OSS free
Funding$78M total Series B · 2026-03$68M total $200M val Series B · 2023-04
Backend storagecustom (Rust-built HNSW + RocksDB metadata)custom (LSM-backed vector + inverted index)
DeploymentBoth (self-hosted + managed cloud) — OSS engine; Qdrant Managed Cloud, Hybrid Cloud and Private CloudBoth (self-hosted + managed cloud) — OSS (Docker/K8s); Weaviate Cloud shared (Free/Flex) and dedicated (Premium)
API surfaceREST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C#REST, GraphQL, gRPC, SDK: Python, JS/TS, Go, Java
EmbeddingBYOmultiple supported
Multi-tenancyHardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gapTenant-per-collection (multi-tenancy feature) gives logical isolation without separate clusters; Dedicated Cloud option for hard isolation
MCPyes — official qdrant/mcp-server-qdrant (GitHub, Apache-2.0)yes — official MCP server built into Weaviate since v1.38 (Streamable HTTP at /v1/mcp)

At a glance

QdrantWeaviate
SectionVector-database infrastructure Vector-database infrastructure
TierT1 T1
TypeVector DB + DBSF + RRF Hybrid vector DB + learned ranking
Created2020-05 2016-03
Latest releasev1.19.2 (2026-10-05) v1.40.2 (2026-10-21)
LicenseApache-2.0 BSD-3-Clause
GitHubqdrant/qdrant — ~34.9k stars, last commit 2026-10 weaviate/weaviate — ~16.8k stars, last commit 2026-10
PricingFree tier forever (single node, 1 GB RAM / 4 GB disk); Standard usage-based hourly billing; Premium has minimum spend; Hybrid/Private Cloud via sales Free cluster $0 (100k objects, 1 GB RAM, 10 GB disk); Flex pay-as-you-go from $45/mo; Premium prepaid via sales; OSS free
Funding$78M total Series B · 2026-03 $68M total $200M val Series B · 2023-04
Backend storagecustom (Rust-built HNSW + RocksDB metadata) custom (LSM-backed vector + inverted index)
DeploymentBoth (self-hosted + managed cloud) — OSS engine; Qdrant Managed Cloud, Hybrid Cloud and Private Cloud Both (self-hosted + managed cloud) — OSS (Docker/K8s); Weaviate Cloud shared (Free/Flex) and dedicated (Premium)
API surfaceREST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C# REST, GraphQL, gRPC, SDK: Python, JS/TS, Go, Java
EmbeddingBYO multiple supported
Multi-tenancyHardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gap Tenant-per-collection (multi-tenancy feature) gives logical isolation without separate clusters; Dedicated Cloud option for hard isolation
MCPyes — official qdrant/mcp-server-qdrant (GitHub, Apache-2.0) yes — official MCP server built into Weaviate since v1.38 (Streamable HTTP at /v1/mcp)
A2Ano Google A2A (Agent2Agent) integration documented as of 2026-05. no Google A2A (Agent2Agent) integration documented as of 2026-05.
OpenTelemetryfirst-class — Prometheus + OTel first-class — Prometheus + OTel
Optimised forlow-latency similarity search + scale low-latency similarity search + scale
Anti-fitnot for relational / graph-heavy queries (vector-first by design) not for relational / graph-heavy queries (vector-first by design)

Pros & cons

Qdrant

Pros: Rust-built — fastest of the OSS vector DBs in many benchmarks; strong filtering and hybrid search; clean API.

Cons: Smaller managed-cloud presence than Pinecone; ecosystem of integrations still maturing relative to Weaviate.

Weaviate

Pros: OSS-first managed and self-hosted vector DB with native hybrid (vector + keyword) and module ecosystem (Q&A, summarization, classification).

Cons: Module surface area can lead to feature drift; smaller enterprise sales presence than Pinecone.

Rows last verified 2026-10-26 / 2026-10-26. Data is CC-BY-4.0 — see how to read this.