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Saturday, May 24, 2025

QDrant and WebVeta

Introduction to Qdrant and Its Use in WebVeta

Qdrant is an open-source vector similarity search engine designed for storing, managing, and efficiently querying high-dimensional vector data. Unlike traditional databases that handle structured data, Qdrant is built specifically for unstructured data represented as vectors—such as text embeddings.

What is Qdrant?

Qdrant is a production-ready database that provides a convenient API for storing, searching, and managing “points”—each of which consists of a vector (a numerical representation of data) and an optional payload (additional metadata). These points are organized into collections, where each collection contains vectors of the same dimensionality and uses a single distance metric to measure similarity.

Key Features of Qdrant

·        Vector Similarity Search: Qdrant excels at finding similar items in large datasets by comparing vector distances, a process known as approximate nearest neighbor (ANN) search.

·        Payload Filtering: Each vector can carry a JSON payload, allowing you to filter search results based on metadata such as tags, categories, or timestamps.

·        High Performance: Written in Rust, Qdrant is fast, reliable, and can handle high throughput and real-time updates.

·        Horizontal Scaling: Qdrant supports distributed deployments, making it scalable for large-scale applications.

·        Advanced Indexing: Uses HNSW (Hierarchical Navigable Small World) graphs for efficient ANN search in high-dimensional spaces.

·        Hybrid Search: Combines semantic similarity with structured filtering for more precise results.

How Qdrant Works

Qdrant organizes data into collections, where each collection contains points. Each point is a vector with an optional payload. When you perform a search, Qdrant uses the chosen distance metric (such as cosine similarity) to find the most similar vectors to your query. You can also filter results using the payload metadata, enabling complex, hybrid queries that combine semantic similarity with business logic.

Storage Options

·        In-memory: All vectors are stored in RAM for maximum speed, with disk access only for persistence.

·        Memmap: Uses a memory-mapped file for storage, balancing speed and memory usage[1].

Qdrant in WebVeta

WebVeta is a SaaS platform that leverages Qdrant to power advanced search. By integrating Qdrant, WebVeta can efficiently handle large volumes of unstructured data and content embeddings—and deliver fast, accurate similarity searches.

Use Cases in WebVeta

·        Semantic Search: Users can find relevant content by searching for meaning rather than just keywords, thanks to Qdrant’s vector-based search capabilities.

 

Using WebVeta any website can have semantic search using 2 – 3 lines of plain HTML! WebVeta uses multiple optimizations and multiple methods for increasing accuracy of search.

Sign up -> https://webveta.alightservices.com/

 

Conclusion

Qdrant is a modern, scalable, and efficient vector search engine that is well-suited for SaaS platforms like WebVeta. Its ability to handle high-dimensional data, and scale horizontally makes it an invaluable tool for building advanced search systems.

 


 Contact me for a free trial or sign-up: https://webveta.alightservices.com/

 

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Best regards,

Mr. Kanti Arumilli 


I don’t have any fake aliases, nor any virtual aliases like some of the the psycho spy R&AW traitors of India. NOT associated with the “ass”, “es”, “eka”, “ok”, “okay”, “is”, erra / yerra karan, kamalakar, diwakar, kareem, karan, erra / yerra sowmya, erra / yerra, zinnabathuni, bojja srinivas (was a friend and batchmate 1998 – 2002, not anymore – if he joined Mafia), mukesh golla (was a friend and classmate 1998 – 2002, if he joined Mafia), erra, erra, thota veera, uttam’s, bandhavi’s, bhattaru’s, thota’s, bojja’s, bhattaru’s or Arumilli srinivas or Arumilli uttam(may be they are part of a different Arumilli family – not my Arumilli family).




 

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QDrant and WebVeta

Introduction to Qdrant and Its Use in WebVeta Qdrant is an open-source vector similarity search engine designed for storing, managing, and e...