---
title: "pgvector vs pgvecto.rs"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/pgvector-pgvector-vs-tensorchord-pgvecto-rs"
tools: ["pgvector-pgvector", "tensorchord-pgvecto-rs"]
---

# pgvector vs pgvecto.rs

Neutral, constraint-first comparison with live GitHub stats.

| | [pgvector](/tools/pgvector-pgvector.md) | [pgvecto.rs](/tools/tensorchord-pgvecto-rs.md) |
| --- | --- | --- |
| Tagline | Open-source vector similarity search for Postgres | Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres |
| Stars | 22,112 | 2,177 |
| Forks | 1,233 | 84 |
| Open issues | 14 | 76 |
| Language | C | Rust |
| Adopt for | <ul><li><strong>Open-source vector similarity search:</strong> pgvector extends PostgreSQL for exact and approximate nearest neighbor search on various types of vectors.</li><li><strong>C-based library:</strong> Written, | `pgvecto.rs` is a Postgres extension designed for vector similarity search, written in Rust and supporting up to 65535 dimensions. It introduces advanced features such as VBASE method for hybrid vector-relational queries |
| Persona | - | - |
| Runtime | - | - |
| License | Other | Apache-2.0 |
| Categories | Vector Databases | Vector Databases |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [pgvector](/tools/pgvector-pgvector.md) | [pgvecto.rs](/tools/tensorchord-pgvecto-rs.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 0d | 496d |
| Open issues (now) | 14 | 76 |
| Security scan | No lockfile | Not scanned |
| Full report | [trust report](/tools/pgvector-pgvector/trust.md) | [trust report](/tools/tensorchord-pgvecto-rs/trust.md) |

**Typed relationship:** pgvector _(alternative)_ pgvecto.rs

pgvecto.rs offers a similar service to pgvector for performing vector searches on PostgreSQL, but it provides an alternative approach with some differences in scalability and hybrid search capabilities.

## Decision facts: pgvector

- **Adopt for:** <ul><li><strong>Open-source vector similarity search:</strong> pgvector extends PostgreSQL for exact and approximate nearest neighbor search on various types of vectors.</li><li><strong>C-based library:</strong> Written,

## Decision facts: pgvecto.rs

- **Adopt for:** `pgvecto.rs` is a Postgres extension designed for vector similarity search, written in Rust and supporting up to 65535 dimensions. It introduces advanced features such as VBASE method for hybrid vector-relational queries

## Choose when

### Choose pgvector if…

- pgvector is primarily C; pgvecto.rs is Rust.
- License: pgvector is Other, pgvecto.rs is Apache-2.0.
- pgvecto.rs offers a similar service to pgvector for performing vector searches on PostgreSQL, but it provides an alternative approach with some differences in scalability and hybrid search capabilities.
- Tags unique to pgvector: approximate-nearest-neighbor-search, nearest-neighbor-search.
- pgvector ships Docker support for self-hosted deployment.
- You prefer an open-source solution for integrating vector similarity search with existing Postgres databases, offering ACID compliance and robust data management features.

### Choose pgvecto.rs if…

- pgvecto.rs is primarily Rust; pgvector is C.
- License: pgvecto.rs is Apache-2.0, pgvector is Other.
- pgvecto.rs offers a similar service to pgvector for performing vector searches on PostgreSQL, but it provides an alternative approach with some differences in scalability and hybrid search capabilities.
- Tags unique to pgvecto.rs: postgresql, rust, vector-search.
- - **When high dimensionality support is required**: Supports up to 65535 dimensions which can be crucial if the use case involves very dense or complex feature spaces

## When NOT to use pgvector

- You are working on Windows environments without access to C++ support tools required for native compilation; alternative installation methods like Docker might introduce additional setup complexity.
- Your project requires real-time search operations with extremely low latency that may not be fully satisfied by the PostgreSQL infrastructure underlying pgvector.

## When NOT to use pgvecto.rs

- - **If you prioritize stability over cutting-edge features**: Developers have pointed to a newer implementation named VectorChord which is said to offer superior stability; consider migrating if long-

## Common questions

### What is the difference between pgvector and pgvecto.rs?

pgvector: Open-source vector similarity search for Postgres. pgvecto.rs: Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. See the comparison table for live GitHub stats and shared categories.

### When should I choose pgvector over pgvecto.rs?

Choose pgvector over pgvecto.rs when pgvector is primarily C; pgvecto.rs is Rust; License: pgvector is Other, pgvecto.rs is Apache-2.0; pgvecto.rs offers a similar service to pgvector for performing vector searches on PostgreSQL, but it provides an alternative approach with some differences in scalability and hybrid search capabilities; Tags unique to pgvector: approximate-nearest-neighbor-search, nearest-neighbor-search; pgvector ships Docker support for self-hosted deployment; You prefer an open-source solution for integrating vector similarity search with existing Postgres databases, offering ACID compliance and robust data management features.

### When should I choose pgvecto.rs over pgvector?

Choose pgvecto.rs over pgvector when pgvecto.rs is primarily Rust; pgvector is C; License: pgvecto.rs is Apache-2.0, pgvector is Other; pgvecto.rs offers a similar service to pgvector for performing vector searches on PostgreSQL, but it provides an alternative approach with some differences in scalability and hybrid search capabilities; Tags unique to pgvecto.rs: postgresql, rust, vector-search; - **When high dimensionality support is required**: Supports up to 65535 dimensions which can be crucial if the use case involves very dense or complex feature spaces.

### When should I avoid pgvector?

You are working on Windows environments without access to C++ support tools required for native compilation; alternative installation methods like Docker might introduce additional setup complexity. Your project requires real-time search operations with extremely low latency that may not be fully satisfied by the PostgreSQL infrastructure underlying pgvector.

### When should I avoid pgvecto.rs?

- **If you prioritize stability over cutting-edge features**: Developers have pointed to a newer implementation named VectorChord which is said to offer superior stability; consider migrating if long-

### Is pgvector or pgvecto.rs more popular on GitHub?

pgvector has more GitHub stars (22,112 vs 2,177). Stars measure visibility, not whether either tool fits your constraints.

### Are pgvector and pgvecto.rs open source?

Yes - both are open-source projects on GitHub (pgvector: Other, pgvecto.rs: Apache-2.0).

### Where can I find alternatives to pgvector or pgvecto.rs?

GraphCanon lists graph-backed alternatives at /tools/pgvector-pgvector/alternatives and /tools/tensorchord-pgvecto-rs/alternatives (/tools/pgvector-pgvector/alternatives.md, /tools/tensorchord-pgvecto-rs/alternatives.md), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at /compare/pgvector-pgvector-vs-tensorchord-pgvecto-rs.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, pgvector or pgvecto.rs?

pgvector: Very active. pgvecto.rs: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for pgvector and pgvecto.rs?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pgvector: /tools/pgvector-pgvector/trust; pgvecto.rs: /tools/tensorchord-pgvecto-rs/trust.

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=pgvector-pgvector`](/api/graphcanon/graph?tool=pgvector-pgvector)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_