pgvector vs Weaviate
pgvector vs Weaviate: side-by-side comparison of two vector-database infrastructure systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| pgvector | Weaviate | |
|---|---|---|
| Cost tier | free | free |
| $/Mtok input | 0 | 0 |
| $/Mtok output | 0 | 0 |
Where they differ (15)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| pgvector | Weaviate | |
|---|---|---|
| Type | PostgreSQL vector extension | Hybrid vector DB + learned ranking |
| Created | 2021-04 | 2016-03 |
| Latest release | v0.8.6 (2026-07-29) | v1.40.2 (2026-10-21) |
| License | PostgreSQL | BSD-3-Clause |
| GitHub | pgvector/pgvector — ~23.5k stars, last commit 2026-07 or later (0.8.7 unreleased) | weaviate/weaviate — ~16.8k stars, last commit 2026-10 |
| Pricing | free (OSS) | 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 | No external funding — open-source project by independent developer | $68M total $200M val Series B · 2023-04 |
| Backend storage | Postgres | custom (LSM-backed vector + inverted index) |
| Deployment | Self-hosted only — PostgreSQL extension; also offered inside managed Postgres (Supabase, AWS RDS, Azure, Neon, etc.) | Both (self-hosted + managed cloud) — OSS (Docker/K8s); Weaviate Cloud shared (Free/Flex) and dedicated (Premium) |
| API surface | SQL via Postgres protocol | REST, GraphQL, gRPC, SDK: Python, JS/TS, Go, Java |
| Embedding | BYO | multiple supported |
| Multi-tenancy | Logical isolation via Postgres schemas/databases; managed providers (Supabase, Neon, RDS) add tenant-level controls | Tenant-per-collection (multi-tenancy feature) gives logical isolation without separate clusters; Dedicated Cloud option for hard isolation |
| MCP | yes — community Postgres MCP servers with pgvector tools (e.g. MOmayr/mcp-postgres-pgvector) | yes — official MCP server built into Weaviate since v1.38 (Streamable HTTP at /v1/mcp) |
| A2A | not supported | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | via Postgres OTel | first-class — Prometheus + OTel |
At a glance
| pgvector | Weaviate | |
|---|---|---|
| Section | Vector-database infrastructure | Vector-database infrastructure |
| Tier | T1 | T1 |
| Type | PostgreSQL vector extension | Hybrid vector DB + learned ranking |
| Created | 2021-04 | 2016-03 |
| Latest release | v0.8.6 (2026-07-29) | v1.40.2 (2026-10-21) |
| License | PostgreSQL | BSD-3-Clause |
| GitHub | pgvector/pgvector — ~23.5k stars, last commit 2026-07 or later (0.8.7 unreleased) | weaviate/weaviate — ~16.8k stars, last commit 2026-10 |
| Pricing | free (OSS) | 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 | No external funding — open-source project by independent developer | $68M total $200M val Series B · 2023-04 |
| Backend storage | Postgres | custom (LSM-backed vector + inverted index) |
| Deployment | Self-hosted only — PostgreSQL extension; also offered inside managed Postgres (Supabase, AWS RDS, Azure, Neon, etc.) | Both (self-hosted + managed cloud) — OSS (Docker/K8s); Weaviate Cloud shared (Free/Flex) and dedicated (Premium) |
| API surface | SQL via Postgres protocol | REST, GraphQL, gRPC, SDK: Python, JS/TS, Go, Java |
| Embedding | BYO | multiple supported |
| Multi-tenancy | Logical isolation via Postgres schemas/databases; managed providers (Supabase, Neon, RDS) add tenant-level controls | Tenant-per-collection (multi-tenancy feature) gives logical isolation without separate clusters; Dedicated Cloud option for hard isolation |
| MCP | yes — community Postgres MCP servers with pgvector tools (e.g. MOmayr/mcp-postgres-pgvector) | yes — official MCP server built into Weaviate since v1.38 (Streamable HTTP at /v1/mcp) |
| A2A | not supported | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | via Postgres OTel | first-class — Prometheus + OTel |
| Optimised for | low-latency similarity search + scale | low-latency similarity search + scale |
| Anti-fit | not for relational / graph-heavy queries (vector-first by design) | not for relational / graph-heavy queries (vector-first by design) |
Pros & cons
pgvector
Pros: Postgres extension — keeps vector data alongside transactional data with full ACID; minimal ops for shops already running Postgres.
Cons: Performance plateau at very large vector counts; limited filter pushdown vs purpose-built engines.
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.