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Qdrant Multi Node Cluster

Qdrant Multi Node Cluster is an open-source deployment project demonstrating a distributed Qdrant vector database, with Docker Compose configuration, Prometheus and Grafana monitoring, and a Python client demo.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Qdrant Multi Node Cluster — OpenViST project profile in AI Infrastructure & Serving.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you need a documented starting point for a self-hosted, multi-node Qdrant deployment and want a Python demo and monitoring configuration alongside it.

Who it is for

  • Developers building self-hosted similarity-search infrastructure.
  • Teams evaluating vector retrieval for semantic search or chatbot knowledge bases.
  • Operators who want an example of monitoring a multi-node Qdrant deployment.

Documented uses

  • Deploy Qdrant across multiple nodes using Docker Compose.
  • Demonstrate Python-client interaction with the cluster.
  • Collect and visualize cluster metrics with Prometheus and Grafana.
  • Adapt sharding and vector collection settings for a search workload.
Before you choose

Requirements & limits

The repository is public and specifies an MIT license. The documented deployment requires Docker, Docker Compose, Python 3.8+, and Git.

  • Deployment is centered on Docker Compose and self-hosted services.
  • Prometheus and Grafana are included for metrics collection and visualization.
  • The README demonstrates at least three Qdrant nodes and shows an example for adding another node.
  • The demo supports host, port, and point-count parameters; the README lists Qdrant, Prometheus, and Grafana local endpoints.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the documented Qdrant cluster

Install the project and start its Docker Compose cluster with monitoring.

Before you start

  • Docker and Docker Compose
  • Python 3.8+
  • Git

Steps

  1. Clone the repository and change into its directory.

  2. Install the package and dependencies with the command below.

    Documented command
    pip install -e .

  3. Change to deployments/docker and run docker-compose up -d.

Expected outcome

The documented setup starts the Qdrant cluster alongside Prometheus and Grafana.

Guide limitations

  • The README lists local service endpoints but does not document workload-specific production sizing or configuration in this quick-start sequence.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
Qdrant Multi Node ClusterDeploy Qdrant across multiple nodes using Docker Compose.Docker, Self-hosted, ServerThe repository is public and specifies an MIT license. The documented deployment requires Docker, Docker Compose, Python 3.8+, and Git.
LlmakerProvision a model together with vector search, embeddings, caching or observability services.CLI, Docker, Self-hostedThe README requires Docker and lists Linux and macOS for prebuilt binaries. It also documents installation through Go or from source. The project is labeled alpha.
Weaviate — weaviateStore application objects alongside vectors and retrieve similar items.Cloud, Self-hosted, ServerThe repository describes Weaviate as open source and lists Docker, Kubernetes and Weaviate Cloud deployment options.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
Mohitkr95/qdrant-multi-node-cluster · Official homepage title · retained in its source language
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