dhi.io/pgvector
pgvector
PostgreSQL with the pgvector extension for open-source vector similarity search.
pushed 10 hours ago
linux/amd64, linux/arm64
201.45 MB
for linux/amd64
173
for linux/amd64
Active support
until Nov 2027
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Build Level 3
Tamper-evident proof of how and from what sources this image was built. Build Level 3 is the highest the SLSA build track defines.
CycloneDX SBOM + SPDX SBOM
A software bill of materials in both CycloneDX and SPDX formats so it drops straight into your existing tooling. Audit exactly what you're shipping.
A Vulnerability Exploitability exchange document, Docker's assessment of which CVEs actually affect this image and which don't apply, so you can focus on real risk instead of chasing false positives.
Available
A link to everything used to build the image, package source code, Git repos, and build files, so you can audit or reproduce the build and stay compliant with open source licenses.
Every known vulnerability in this image, shown in full rather than hidden. The VEX data flags which ones actually apply, so you can tell real exposure from noise before you ship.
Exactly what changed in this build, down to the package bumps and fixes behind the version you're pulling.
Verifies no keys, tokens, or credentials were accidentally baked into the image.
The image layers were scanned for known malware signatures before publishing.
About pgvector
pgvector is an open-source vector similarity search extension for PostgreSQL. It adds a vector data type along with
exact and approximate nearest neighbor search, allowing PostgreSQL databases to store and query embeddings produced by
machine learning models. pgvector supports L2 distance, inner product, cosine distance, L1 distance, Hamming distance,
and Jaccard distance, with HNSW and IVFFlat indexes for fast approximate search at scale.
This image bundles pgvector with a Docker Hardened PostgreSQL base, providing a turnkey vector database for retrieval augmented generation (RAG), semantic search, recommendation systems, and similarity workloads.
For more information, visit https://github.com/pgvector/pgvector.
About Docker Hardened Images
Docker Hardened Images are built to meet the highest security and compliance standards. They provide a trusted foundation for containerized workloads by incorporating security best practices from the start.
Why use Docker Hardened Images?
These images are published with zero-known CVEs, include signed provenance, and come with a complete Software Bill of Materials (SBOM) and VEX metadata. They're designed to secure your software supply chain while fitting seamlessly into existing Docker workflows.
Trademarks
PostgreSQL® is a trademark of PostgreSQL Community Association of Canada. All rights in the mark are reserved to PostgreSQL Community Association of Canada. Any use by Docker is for referential purposes only and does not indicate sponsorship, endorsement, or affiliation.
pgvector is open-source software distributed under the PostgreSQL License. Use by Docker is for referential purposes only and does not indicate sponsorship, endorsement, or affiliation.