simple, fast, open source

vector database for processing unstructured data

Get started GitHub

Install Vector5db 

npm install --save vector5ai/vector5db

Initialize collection

const db = new Vector5db();
    const collection = db.createCollection('my-collection');

Load sample data

const items: Item[] = [
      { id: '1', vector: [1, 2], metadata: { category: 'A' } },
      { id: '2', vector: [3, 4], metadata: { category: 'A' } },
      { id: '3', vector: [2, 3], metadata: { category: 'B' } },
      // ...
    ];
    
    items.forEach((item) => 
      collection.add(item.id, item.vector, item.metadata, item.document)
    );

Query the nearest item with filtering by category

const query = [2, 3];
    const nearest = collection.query(query, 1, { category: 'A' });

Lightweight and efficient

Our vector database is built with performance in mind. It is a single package with no external dependencies, so it is easy to install and deploy.

Runs on any device

You can use our vector database on your desktop, laptop, or mobile phone.

Multiple distance calculations

Our vector database supports multiple distance calculations, including cosine similarity, euclidean distance, and more.

Nearest neighbor search

DB5 can quickly and efficiently find the nearest neighbors of a given vector. This makes it ideal for applications such as product recommendations, image search, and natural language processing.

Written in TypeScript

Our vector database is written in TypeScript, which gives you the power of static typing. This helps to prevent errors and makes your code more maintainable.

Let's start new adventure with
DB5 VECTOR DATABASE

Our vector database is a powerful and versatile tool that can be used for a variety of applications.

Improve customer satisfaction by Vector Database- Semantic Search

DB5 plays a crucial role in transforming various industries by harnessing the power of vector-based data retrieval and analytics. Some notable applications of vector databases, including DB5, are: E-commerce Solutions: Vector databases like DB5 enable efficient product recommendation systems, enhancing the customer shopping experience and increasing sales conversion rates. By analyzing customer preferences and similarities, businesses can deliver personalized product recommendations and improve customer satisfaction.

Semantic Search:

Vector databases excel in semantic search, enabling users to find relevant information based on the meaning and context of their queries. With DB5's advanced indexing and search capabilities, businesses can implement powerful semantic search functionality to enhance user experiences and drive accurate search results. Computer Security: Vector databases play a vital role in computer security applications.

Created for sensitive data :

By analyzing patterns and identifying anomalies, DB5 can help detect and prevent security threats, safeguarding sensitive data and systems from malicious attacks. Pharmaceuticals and Healthcare: Vector databases have the potential to revolutionize pharmaceutical research and healthcare. By analyzing molecular structures and similarities, DB5 can assist in drug discovery, personalized medicine, and disease diagnosis, accelerating advancements in the field of healthcare.

In conclusion, DB5 offer a powerful solution for efficient data retrieval, analytics, and decision-making. With their scalability, fast similarity search, and support for various industries, vector databases like DB5 are transforming the way businesses handle and extract insights from high-dimensional data. By leveraging DB5's capabilities, organizations can unlock the true value of their data and gain a competitive edge in today's data-driven world.

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