VectorChord

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VectorChord enables scalable and fast vector search directly within Postgres databases. It is designed for efficient storage and retrieval of large vector datasets.

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At a glance

Pricing

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Free tier

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API

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Skill level

Technical

About

What is VectorChord?

VectorChord is a specialized tool engineered for performing scalable and rapid vector searches within a Postgres database environment. It prioritizes disk-friendliness, allowing for the hosting of up to 100 million vectors on a single i4i.xlarge instance. Positioned as the successor to pgvecto.rs, VectorChord aims to provide enhanced performance and efficiency for applications requiring robust vector similarity search capabilities directly integrated with their relational database infrastructure.

Best used for

Integrating high-performance, scalable vector search capabilities directly into a Postgres database for AI and machine learning applications.

Common actions

Perform vector search

Scale vector databases

Integrate AI with Postgres

Optimize data storage

Improve search performance

low-code/no-codeautomated workflowdeepfakeopen-sourcecollaborationworkflowsface swappinggithub copilot"AI Agents"

Capabilities

Key features

Scalable vector search
Fast search
Disk-friendly
Postgres integration
100M+ vectors

Target Audience

Database administratorsBackend developersMachine learning engineersData architects

Integrations

Not yet documented

Pricing & Plans

unknown

Free

FAQs

How does VectorChord compare to pgvecto.rs in terms of performance and features?

VectorChord is designed as the successor to pgvecto.rs, offering enhanced performance and efficiency. While both integrate with Postgres for vector search, VectorChord focuses on improved scalability and disk-friendliness, allowing for a significantly larger vector capacity on a single instance.

What are the hardware requirements for hosting 100 million vectors with VectorChord?

VectorChord is optimized for disk-friendliness, enabling the hosting of up to 100 million vectors on a single i4i.xlarge instance. This specific instance type suggests a focus on high I/O performance and sufficient storage capacity for large vector datasets.

Can VectorChord be used with existing Postgres databases, or does it require a new setup?

VectorChord is engineered to integrate directly within a Postgres database environment. This means it can likely be added to an existing Postgres setup as an extension or a similar mechanism, leveraging your current relational database infrastructure for vector search capabilities.

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AI Agents & Automation › AI Frameworks & Infra Data & Analytics › Data Pipelines & Integration

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