--- title: Qdrant Documentation weight: 10 --- # Documentation **Qdrant (read: quadrant )** is a vector similarity search engine. Use our documentation to develop a production-ready service with a convenient API to store, search, and manage vectors with an additional payload. Qdrant's expanding features allow for all sorts of neural network or semantic-based matching, faceted search, and other applications. ## First-Time Users: There are three ways to use Qdrant: 1. [**Run a Docker image**](quick-start/) if you don't have a Python development environment. Setup a local Qdrant server and storage in a few moments. 2. [**Get the Python client**](https://github.com/qdrant/qdrant-client) if you're familiar with Python. Just `pip install qdrant-client`. The client uses an in-memory database. 3. [**Spin up a Qdrant Cloud cluster:**](cloud/) the recommended method to run Qdrant in production. Read [Quickstart](cloud/cloud-quick-start/) to setup your first instance. ### Recommended Workflow: ![Local mode workflow](https://raw.githubusercontent.com/qdrant/qdrant-client/master/docs/images/try-develop-deploy.png) First, try Qdrant locally using the [Qdrant Client](https://github.com/qdrant/qdrant-client) and with the help of our [Tutorials](tutorials/) and Guides. Develop a sample app from our [Examples](examples/) list and try it using a [Qdrant Docker](guides/installation/) container. Then, when you are ready for production, deploy to a Free Tier [Qdrant Cloud](cloud/) cluster. ## Popular Topics: | Tutorial | Description | Tutorial| Description | |----------------------------------------------------|----------------------------------------------|---------|------------------| | [Installation](guides/installation/) | Different ways to install Qdrant. | [Collections](concepts/collections/) | Learn about the central concept behind Qdrant. | | [Configuration](guides/configuration/) | Update the default configuration. | [Bulk Upload](tutorials/bulk-upload/) | Efficiently upload a large number of vectors. | | [Optimization](tutorials/optimize/) | Optimize Qdrant's resource usage. | [Multitenancy](tutorials/multiple-partitions/) | Setup Qdrant for multiple independent users. | ## Common Use Cases: Qdrant is ideal for deploying applications based on the matching of embeddings produced by neural network encoders. Check out the [Examples](examples/) section to learn more about common use cases. Also, you can visit the [Tutorials](tutorials/) page to learn how to work with Qdrant in different ways. | Use Case | Description | Stack | |-----------------------|----------------------------------------------|--------| | [Intro to Semantic Search and Recommendations Systems](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_getting_started/getting_started.ipynb) | Learn how to get started building semantic search and recommendation systems. | Qdrant | | [Build a Simple Neural Search](tutorials/neural-search/) | Build and deploy a neural search. [Check out the live demo app.](https://demo.qdrant.tech/#/) | Qdrant, BERT, FastAPI | | [Build a Search with Aleph Alpha](tutorials/aleph-alpha-search/) | Build a simple semantic search that combines text and image data. | Qdrant, Aleph Alpha | | [Search and Recommend Newspaper Articles](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_text_data/qdrant_and_text_data.ipynb) | Work with text data to develop a semantic search and a recommendation engine for news articles. | Qdrant | | [Recommendation System for Songs](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_audio_data/03_qdrant_101_audio.ipynb) | Use Qdrant to develop a music recommendation engine based on audio embeddings. | Qdrant | | [Image Comparison System for Skin Conditions](https://colab.research.google.com/github/qdrant/examples/blob/master/qdrant_101_image_data/04_qdrant_101_cv.ipynb) | Use Qdrant to compare challenging images with labels representing different skin diseases. | Qdrant | | [Question and Answer System with LlamaIndex](https://githubtocolab.com/qdrant/examples/blob/master/llama_index_recency/Qdrant%20and%20LlamaIndex%20%E2%80%94%20A%20new%20way%20to%20keep%20your%20Q%26A%20systems%20up-to-date.ipynb) | Combine Qdrant and LlamaIndex to create a self-updating Q&A system. | Qdrant, LlamaIndex, Cohere |