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Description

Qdrant serves as a sophisticated vector similarity engine and database, functioning as an API service that enables the search for the closest high-dimensional vectors. By utilizing Qdrant, users can transform embeddings or neural network encoders into comprehensive applications designed for matching, searching, recommending, and far more. It also offers an OpenAPI v3 specification, which facilitates the generation of client libraries in virtually any programming language, along with pre-built clients for Python and other languages that come with enhanced features. One of its standout features is a distinct custom adaptation of the HNSW algorithm used for Approximate Nearest Neighbor Search, which allows for lightning-fast searches while enabling the application of search filters without diminishing the quality of the results. Furthermore, Qdrant supports additional payload data tied to vectors, enabling not only the storage of this payload but also the ability to filter search outcomes based on the values contained within that payload. This capability enhances the overall versatility of search operations, making it an invaluable tool for developers and data scientists alike.

Description

Achieve optimal results through efficient and adaptable query-time sorting, allowing you to position specific records strategically for enhanced visibility or promotion. Enable users to discover pants when they search for trousers, and vice versa, by setting them as synonyms. Consolidate multiple users’ data within a single index and issue unique API keys to ensure that each user can only access their own information. Dynamically sort records by any field in your documents, such as price or popularity, eliminating the need for duplicate indices. Enhance result diversity by grouping similar items together, like combining all color variations of a shirt into one entry. Retrieve only those records that align with specified filters, and perform aggregate functions to compute counts, minimums, maximums, and averages across your records. Additionally, facilitate search and sorting capabilities within a specified distance from a particular latitude and longitude or within a defined polygon area. By following a few straightforward steps, you can build a robust and reliable production-grade search service that meets your needs. Ultimately, this approach ensures a seamless and efficient user experience, promoting greater satisfaction and engagement.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

IBM watsonx.data
Activepieces
Airtool
Apify
Broxi AI
Cognee
CogniSync
Database Mart
Elestio
FormKiQ
Gatsby
LLMWare.ai
Laravel Herd
OmniMind
OpenLIT
Prem AI
Prepr
ToolJet
WordPress
voyage-code-3

Integrations

IBM watsonx.data
Activepieces
Airtool
Apify
Broxi AI
Cognee
CogniSync
Database Mart
Elestio
FormKiQ
Gatsby
LLMWare.ai
Laravel Herd
OmniMind
OpenLIT
Prem AI
Prepr
ToolJet
WordPress
voyage-code-3

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Qdrant

Founded

2021

Country

Germany

Website

qdrant.tech/

Vendor Details

Company Name

Typesense

Country

United States

Website

typesense.org

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