Promote Sign in Sign up

Vector databases

Supabase Vector ✓

The Postgres Vector database and AI Toolkit

96 views 0 saves Freemium
API Postgres Database Vector Storage
More categories (4)
Data Embedding AI Applications Development Data Indexing Vector databases
Visit website Sign in to save

Free + from $25/mo

Verdict

A quick read before you dig into the full page.

Best if
The Postgres Vector database and AI Toolkit
Skip if
Complex permissions system
Pick this when
Open-source PostgreSQL Vector database

Considering turbopuffer instead? Compare side by side

Overview

Supabase Vector is an open-source Postgres Vector database specifically designed for developing AI applications. Users can employ 'pgvector' to store, index, and access embeddings.

The toolkit is integrated within the Supabase ecosystem and enables the creation of AI applications with tools such as Hugging Face and OpenAI. The Supabase Vector solution encapsulates features and capabilities proven useful for Machine Learning operations, easily connecting to any Language Model-based or embedding API - an illustration includes Hugging Face, SageMaker and others beyond.

The tool is secure and scalable, with compliance to SOC2 Type 2, and an advanced permissions system present. Supabase Vector's global deployment allows users to choose from various globally-distributed data centres or to self-host on personal clouds.

The APIs provided are simple yet powerful, offering easy-to-manage client libraries for vector store operations in Postgres. Furthermore, it provides automatic tagging and detection patterns for data management in the vector store.

The tool integrates vector embeddings storage in the same database with transactional data, resulting in simplifying applications and improving performance.

The platform is highly scalable, designed for high performance and optimum global availability. Additionally, the tool incorporates the open-source feature of Supabase, which increases its portability and facilitates easy migration.

Supabase Vector website

Access & connections

Where you can use Supabase Vector.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Tabular

Output

  • API

Supported features

  • SVG

Pros & cons

Pros

  • Open-source PostgreSQL Vector database
  • Integrated in Supabase ecosystem
  • pgvector for storing embeddings
  • Automatic tagging in vector store
  • Detection patterns for data management
  • Transactional and vector data integration
  • Strong security features
  • SOC2 Type 2 compliant
Show 31 more
  • Advanced permissions system
  • Integration with Hugging Face
  • Integration with SageMaker
  • APIs for vector store operations
  • Scalable and high performance
  • Globally distributed data centres
  • Supports self-hosting
  • Optimum global availability
  • Supports easy migration
  • Enables semantic search
  • Promotes content-based long-term retention
  • Allows image similarity detection
  • Integrated data management
  • Supports millions of vectors
  • Ease of learning with Next.js
  • Automatic database backups
  • No vendor lock-in policy
  • Supports multi-region deployment
  • High vector storage efficiency
  • Scalability from experimentation to production
  • Support for enterprise scaling
  • Comes with documentation
  • Ability to upsert metadata
  • Integrates embedding and transactional data
  • Semantic similarity knowledge base
  • Global fleet configuration
  • Ensures data recoverability
  • Fully managed or self-hosted
  • Embedding storage in PostgreSQL
  • Fully scalable
  • Testimonials from reliableclients

Cons

  • Limited to Postgres database
  • Depends on Supabase ecosystem
  • Complex permissions system
  • Requires manual data centre selection
  • No native support for non-vector data
  • High dependency on external APIs
  • Potentially challenging self-hosting
  • Absence of real-time features
Show 2 more
  • Automatic tagging might cause misclassification
  • Potential issue with transactional data integration

Compare alternatives

Similar tools in the catalog — with a clear reason to open each one.

Why look Offers a public API

Full comparison

Free + from $25/mo

Full comparison

Free + from $99/mo

Full comparison

from $54.00

Full comparison

from $29.99/mo

Full comparison

Why look Typically cheaper

Full comparison

Releases 1

Initial release December 5, 2024 Current
Initial release of Supabase Vector.

FAQ 12

What is Supabase Vector?
Supabase Vector is an open-source Postgres Vector database specifically engineered for developing AI applications. It is integrated within the Supabase ecosystem and encapsulates features and capabilities that are useful for Machine Learning operations. It is designed to easily connect to any Language Model-based or embedding API, and it provides a secure and scalable platform with compliance to SOC2 Type 2.
How is Supabase Vector integrated with the Hugging Face and OpenAI?
Supabase Vector is integrated with Hugging Face and OpenAI through connectors, allowing AI developers to connect to each platform’s APIs. This promotes the creation of AI applications using tools native to these platforms.
What is 'pgvector' in the context of Supabase Vector?
'pgvector' in the context of Supabase Vector is a tool that allows users to store, index, and access embeddings. It is designed to support the operation of vector stores in Postgres, providing the necessary functionality for data management in the vector store.
How secure is Supabase Vector?
Supabase Vector provides a secure platform for storing and managing data. It complies with SOC2 Type 2 standards and comes with an advanced permissions system for user management and data protection.
What does it mean that Supabase Vector is compliant with SOC2 Type 2?
Being compliant with SOC2 Type 2 means that Supabase Vector meets the standards set by the American Institute of Certified Public Accountants (AICPA) for managing customer data based on five 'trust service principles'—security, availability, processing integrity, confidentiality, and privacy. This assures users that their data is being handled securely and responsibly.
Can I choose a preferred data centre with Supabase Vector?
Yes, you can choose a preferred data centre with Supabase Vector. Supabase Vector offers global deployment and allows its users to choose from many globally-distributed data centres, ensuring that businesses can select a data centre location that suits their needs.
What are the client libraries provided by Supabase Vector?
The client libraries provided by Supabase Vector are simple yet powerful tools for managing and querying vector stores in Postgres. While specific library names aren’t given, they are said to be easy-to-use, thereby simplifying the process of vector store operations.
How does Supabase Vector handle data indexing and embedding?
Supabase Vector manages data indexing and embedding through the 'pgvector' tool. This tool enables the storage, indexing, and access of embeddings, which are types of data representations useful in machine learning and AI applications.
Is it possible to self-host with Supabase Vector?
Yes, it is possible to self-host with Supabase Vector. In addition to providing numerous globally distributed data centres for hosting, Supabase Vector offers the freedom for users to self-host on personal clouds, which can contribute to data handling flexibility and control.
How does Supabase Vector's permissions system function?
The permissions system in Supabase Vector enables robust user management and data protection. Specific details about the functionality of this system aren't provided. However, the advanced permissions system is part of its security features that ensure only authorized users can access relevant data.
What is the purpose of automatic tagging in Supabase Vector?
The purpose of automatic tagging in Supabase Vector is data management within the vector store. It facilitates the organization and identification of stored vectors, which can be particularly useful when dealing with large datasets.
How does Supabase Vector improve AI application performance?
Supabase Vector improves AI application performance by integrating vector embeddings storage in the same database with transactional data. This simplifies application architecture and enables more efficient data processing and access, thereby contributing to better performance.
Supabase Vector Free + from $25/mo
Visit website