Qdrant Edge on Qdrant - Vector Database

Quickstart

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Qdrant Edge Quickstart

Install Qdrant Edge

First, install the Python Bindings for Qdrant Edge:

pip install qdrant-edge-py

Create a Storage Directory

A Qdrant Edge Shard stores its data in a local directory on disk. Create the directory if it doesn’t exist yet:

from pathlib import Path

SHARD_DIRECTORY = "./qdrant-edge-directory"

Path(SHARD_DIRECTORY).mkdir(parents=True, exist_ok=True)

Configure the Edge Shard

An Edge Shard is configured with a definition of the dense and sparse vectors that can be stored in the Edge Shard, similar to how you would configure a Qdrant collection. Set up a configuration by creating an instance of EdgeConfig:

On-Device Embeddings

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

On-Device Embeddings with Qdrant Edge and FastEmbed

To generate embeddings for use with Qdrant Edge directly on a device, you can use the FastEmbed library. FastEmbed provides multimodal models that run efficiently on edge devices to generate vector embeddings from text and images.

Provision the Device

Assuming the devices on which you will run Qdrant Edge have intermittent or no internet connectivity, you need to provision them with the necessary dependencies and model files ahead of time. First, install FastEmbed and the Qdrant Edge Python bindings:

Data Synchronization Patterns

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Data Synchronization Patterns

This page describes patterns for synchronizing data between Qdrant Edge Shards and Qdrant server collections. For a practical end-to-end guide on implementing these patterns, refer to the Qdrant Edge Synchronization Guide.

Initialize Edge Shard from Existing Qdrant Collection

Instead of starting with an empty Edge Shard, you may want to initialize it with pre-existing data from a collection on a Qdrant server. You can achieve this by restoring a snapshot of a shard in the server-side collection.

Synchronize with a Server

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Synchronize Qdrant Edge with a Server

Qdrant Edge can be synchronized with a collection from an external Qdrant server to support use cases like:

Offload indexing: Indexing is a computationally expensive operation. By synchronizing an Edge Shard with a server collection, you can offload the indexing process to a more powerful server instance. The indexed data can then be synchronized back to the Edge Shard.
Back up and Restore: Regularly back up your Edge Shard data to a central Qdrant instance to prevent data loss. In case of hardware failure or data corruption on the edge device, you can restore the data from the central instance.
Data Aggregation: Collect data from multiple Edge Shards deployed in different locations and aggregate it into a central Qdrant instance for comprehensive analysis and reporting.
Synchronization between devices: Keep data consistent across multiple edge devices by synchronizing their Edge Shards with a central Qdrant instance.

Synchronizing Qdrant Edge with a Server

To support having local updates from the device as well as updates from a server, you can implement a setup with two Edge Shards: