Comparison
pgvector vs turbovec
Verdict
Pick pgvector if pgvector is an extension for PostgreSQL that enables efficient vector similarity search using various distance metrics, including L2, inner product, cosine distance, and L1 distance; pick turbovec if turbovec is a Rust-based vector indexing library with Python bindings that offers significant memory savings and fast SIMD search capabilities, built on Google Research's TurboQuant algorithm.
Markdown twin · pgvector alternatives · turbovec alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | pgvector | turbovec |
|---|---|---|
| Maintenance | Active (7d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Aug 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Aug 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- pgvector
- Open-source vector similarity search for Postgres
- turbovec
- A vector index built on TurboQuant, written in Rust with Python bindings
Stars
- pgvector
- 23k
- turbovec
- 15k
Forks
- pgvector
- 1.3k
- turbovec
- 1.3k
Open issues
- pgvector
- 16
- turbovec
- 17
Language
- pgvector
- C
- turbovec
- Rust
Adopt for
- pgvector
- pgvector is an extension for PostgreSQL that enables efficient vector similarity search using various distance metrics, including L2, inner product, cosine distance, and L1 distance.
- turbovec
- turbovec is a Rust-based vector indexing library with Python bindings that offers significant memory savings and fast SIMD search capabilities, built on Google Research's TurboQuant algorithm.
Persona
- pgvector
- -
- turbovec
- -
Runtime
- pgvector
- -
- turbovec
- -
License
- pgvector
- Other
- turbovec
- MIT
Last pushed
- pgvector
- Sep 10, 2026
- turbovec
- Aug 18, 2026
Categories
- pgvector
- Vector Databases
- turbovec
- Vector Databases
Trust and health
Maintenance
- pgvector
- Active (82%)
- turbovec
- Very active (96%)
Days since push
- pgvector
- 7d
- turbovec
- 0d
Open issues (now)
- pgvector
- 16
- turbovec
- 17
Stars delta
- pgvector
- +674 (30d)
- turbovec
- +1.3k (30d)
Open issues delta
- pgvector
- +2 (30d)
- turbovec
- -14 (30d)
Owner type
- pgvector
- Organization
- turbovec
- User
Full report
- pgvector
- Trust report
- turbovec
- Trust report
Typed relationship
Choose pgvector if…
- pgvector is primarily C; turbovec is Rust.
- License: pgvector is Other, turbovec is MIT.
- turbovec addresses the problem of vector searches similarly to pgvector but within different systems, where turbovec is standalone and pgvector integrates vector indexing capabilities into PostgreSQL.
- Tags unique to pgvector: approximate-nearest-neighbor-search, c-language, docker-support, l2-distance.
- pgvector ships Docker support for self-hosted deployment.
- When you need to perform vector similarity searches within a PostgreSQL database and require support for multiple distance metrics.
When NOT to use pgvector
- If your application does not require the full feature set of PostgreSQL and you are looking for a lightweight solution specifically designed for vector similarity searches.
- When you need real-time, low-latency vector similarity searches that might be better served by specialized vector databases or in-memory solutions.
- If you are working in an environment where PostgreSQL is not supported or where you need to integrate with a different database system.
- When you require a solution that supports more advanced indexing techniques or approximate nearest neighbor search algorithms that are not natively supported by pgvector.
Choose turbovec if…
- turbovec is primarily Rust; pgvector is C.
- License: turbovec is MIT, pgvector is Other.
- turbovec addresses the problem of vector searches similarly to pgvector but within different systems, where turbovec is standalone and pgvector integrates vector indexing capabilities into PostgreSQL.
- Tags unique to turbovec: ann, avx512, embedding, embeddings.
- - Use turbovec when you need to save substantial amounts of memory; for instance, a 10 million document corpus can fit in 4 GB RAM instead of the typical 31 GB with float32.
When NOT to use turbovec
- - Avoid using turbovec in environments where the hardware architecture does not support specific SIMD instructions (like NEON on ARM and AVX-512BW on x86), as this can lead to performance degradation.
- - Do not use it if your application requires external managed services for vector indexing, as turbovec is designed for local deployments without data leaving the machine or VPC.
- - Avoid if you require high precision beyond what 4-bit quantization (or lower bit-widths depending on the configuration) offers.
- - Refrain from using turbovec in scenarios where the lack of a training phase leads to suboptimal performance, as it might not adapt well to certain datasets that benefit from such pre-processing.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (pgvector/pgvector) · observed Sep 20, 2026
- GitHub forks (pgvector/pgvector) · observed Sep 20, 2026
- Last push (pgvector/pgvector) · observed Sep 10, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (RyanCodrai/turbovec) · observed Sep 20, 2026
- GitHub forks (RyanCodrai/turbovec) · observed Sep 20, 2026
- Last push (RyanCodrai/turbovec) · observed Aug 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: pgvector 23k · turbovec 15k (synced Sep 20, 2026).
Common questions
- What is the difference between pgvector and turbovec?
- pgvector: Open-source vector similarity search for Postgres. turbovec: A vector index built on TurboQuant, written in Rust with Python bindings. See the comparison table for live GitHub stats and shared categories.
- When should I choose pgvector over turbovec?
- Choose pgvector over turbovec when pgvector is primarily C; turbovec is Rust; License: pgvector is Other, turbovec is MIT; turbovec addresses the problem of vector searches similarly to pgvector but within different systems, where turbovec is standalone and pgvector integrates vector indexing capabilities into PostgreSQL; Tags unique to pgvector: approximate-nearest-neighbor-search, c-language, docker-support, l2-distance; pgvector ships Docker support for self-hosted deployment; When you need to perform vector similarity searches within a PostgreSQL database and require support for multiple distance metrics.
- When should I choose turbovec over pgvector?
- Choose turbovec over pgvector when turbovec is primarily Rust; pgvector is C; License: turbovec is MIT, pgvector is Other; turbovec addresses the problem of vector searches similarly to pgvector but within different systems, where turbovec is standalone and pgvector integrates vector indexing capabilities into PostgreSQL; Tags unique to turbovec: ann, avx512, embedding, embeddings; - Use turbovec when you need to save substantial amounts of memory; for instance, a 10 million document corpus can fit in 4 GB RAM instead of the typical 31 GB with float32.
- When should I avoid pgvector?
- If your application does not require the full feature set of PostgreSQL and you are looking for a lightweight solution specifically designed for vector similarity searches. When you need real-time, low-latency vector similarity searches that might be better served by specialized vector databases or in-memory solutions. If you are working in an environment where PostgreSQL is not supported or where you need to integrate with a different database system. When you require a solution that supports more advanced indexing techniques or approximate nearest neighbor search algorithms that are not natively supported by pgvector.
- When should I avoid turbovec?
- - Avoid using turbovec in environments where the hardware architecture does not support specific SIMD instructions (like NEON on ARM and AVX-512BW on x86), as this can lead to performance degradation. - Do not use it if your application requires external managed services for vector indexing, as turbovec is designed for local deployments without data leaving the machine or VPC. - Avoid if you require high precision beyond what 4-bit quantization (or lower bit-widths depending on the configuration) offers. - Refrain from using turbovec in scenarios where the lack of a training phase leads to suboptimal performance, as it might not adapt well to certain datasets that benefit from such pre-processing.
- Is pgvector or turbovec more popular on GitHub?
- pgvector has more GitHub stars (23,049 vs 14,822). Stars measure visibility, not whether either tool fits your constraints.
- Are pgvector and turbovec open source?
- Yes - both are open-source projects on GitHub (pgvector: Other, turbovec: MIT).
- Where can I find alternatives to pgvector or turbovec?
- GraphCanon lists graph-backed alternatives at pgvector alternatives and turbovec alternatives (pgvector markdown twin, turbovec markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, pgvector or turbovec?
- pgvector: Active. turbovec: Very active. 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 turbovec?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pgvector trust report; turbovec trust report.