lukawskikacper/qdrant-landing-page-2024-06-21 huggingface dataset:
qdrant-landing/content/documentation/community-links.md

---
title: Community links
weight: 42
---

# Community Contributions

Though we do not officially maintain this content, we still feel that is is valuable and thank our dedicated contributors. 

| Link | Description                  | Stack  |   
|------|------------------------------|--------|
| [Pinecone to Qdrant Migration](https://github.com/NirantK/qdrant_tools)       | Complete python toolset that supports migration between two products.       | Qdrant, Pinecone |  
| [LlamaIndex Support for Qdrant](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/QdrantIndexDemo.html)   | Documentation on common integrations with LlamaIndex.    | Qdrant, LlamaIndex |   
| [Geo.Rocks Semantic Search Tutorial](https://geo.rocks/post/qdrant-transformers-js-semantic-search/)           | Create a fully working semantic search stack with a built in search API and a minimal stack.  | Qdrant, HuggingFace, SentenceTransformers, transformers.js |
qdrant-landing/content/documentation/contribution-guidelines.md

---
title: Contribution Guidelines
weight: 35
draft: true
---

# How to contribute

If you are a Qdrant user - Data Scientist, ML Engineer, or MLOps, the best contribution would be the feedback on your experience with Qdrant.
Let us know whenever you have a problem, face an unexpected behavior, or see a lack of documentation.
You can do it in any convenient way - create an [issue](https://github.com/qdrant/qdrant/issues), start a [discussion](https://github.com/qdrant/qdrant/discussions), or drop up a [message](https://discord.gg/tdtYvXjC4h).
If you use Qdrant or Metric Learning in your projects, we'd love to hear your story! Feel free to share articles and demos in our community.

For those familiar with Rust - check out our [contribution guide](https://github.com/qdrant/qdrant/blob/master/CONTRIBUTING.md).
If you have problems with code or architecture understanding - reach us at any time.
Feeling confident and want to contribute more? - Come to [work with us](https://qdrant.join.com/)!
qdrant-landing/content/documentation/roadmap.md

---
title: Roadmap
weight: 32
draft: true
---

# Qdrant 2023 Roadmap

Goals of the release:

* **Maintain easy upgrades** - we plan to keep backward compatibility for at least one major version back. 
  * That means that you can upgrade Qdrant without any downtime and without any changes in your client code within one major version.
  * Storage should be compatible between any two consequent versions, so you can upgrade Qdrant with automatic data migration between consecutive versions.
* **Make billion-scale serving cheap** - qdrant already can serve billions of vectors, but we want to make it even more affordable.
* **Easy scaling** - our plan is to make it easy to dynamically scale Qdrant, so you could go from 1 to 1B vectors seamlessly.
* **Various similarity search scenarios** - we want to support more similarity search scenarios, e.g. sparse search, grouping requests, diverse search, etc.

## Milestones

* :atom_symbol: Quantization support
  * [ ] Scalar quantization f32 -> u8 (4x compression)
  * [ ] Advanced quantization (8x and 16x compression)
  * [ ] Support for binary vectors

---

* :arrow_double_up: Scalability
  * [ ] Automatic replication factor adjustment
  * [ ] Automatic shard distribution on cluster scaling
  * [ ] Repartitioning support

---

* :eyes: Search scenarios
  * [ ] Diversity search - search for vectors that are different from each other
  * [ ] Sparse vectors search - search for vectors with a small number of non-zero values
  * [ ] Grouping requests - search within payload-defined groups
  * [ ] Different scenarios for recommendation API

---
    
* Additionally
  * [ ] Extend full-text filtering support
    * [ ] Support for phrase queries
    * [ ] Support for logical operators
  * [ ] Simplify update of collection parameters
qdrant-landing/content/documentation/cloud/_index.md

---
title: Managed Cloud
weight: 14
aliases:
  - /documentation/overview/qdrant-alternatives/documentation/cloud/
---

# About Qdrant Managed Cloud

Qdrant Managed Cloud is our SaaS (software-as-a-service) solution, providing managed Qdrant database clusters on the cloud. We provide you the same fast and reliable similarity search engine, but without the need to maintain your own infrastructure.

Transitioning to the Managed Cloud version of Qdrant does not change how you interact with the service. All you need is a [Qdrant Cloud account](https://qdrant.to/cloud/) and an [API key](/documentation/cloud/authentication/) for each request.

You can also attach your own infrastructure as a Hybrid Cloud Environment. For details, see our [Hybrid Cloud](/documentation/hybrid-cloud/) documentation.

## Cluster configuration

Each database cluster comes pre-configured with the following tools, features, and support services:

- Allows the creation of highly available clusters with automatic failover.
- Supports upgrades to later versions of Qdrant as they are released.
- Upgrades are zero-downtime on highly available clusters.
- Includes monitoring and logging to observe the health of each cluster.
- Horizontally and vertically scalable.
- Available natively on AWS and GCP, and Azure. 
- Available on your own infrastructure and other providers if you use the Hybrid Cloud.

## Getting started with Qdrant Managed Cloud

To use Qdrant Managed Cloud, you need at least one cluster. You can create one in the following ways:

1. [**Create a Free Tier cluster**](/documentation/cloud/quickstart-cloud/) with one node and a default configuration (1 GB RAM, 0.5 CPU and 4 GB Disk). This option is perfect for prototyping. You don't need a credit card to join.
2. [**Configure a custom cluster**](/documentation/cloud/create-cluster/) with additional nodes and resources. For this option, you need billing information.

If you're testing Qdrant, We recommend the Free Tier cluster. The capacity should be enough to serve up to 1 M vectors of 768 dimensions. To calculate your needs, refer to our documentation on [Capacity and sizing](/documentation/cloud/capacity-sizing/).

## Support & Troubleshooting

All Qdrant Cloud users are welcome to join our [Discord community](https://qdrant.to/discord/). Our Support Engineers are available to help you anytime.

Paid customers can also contact support directly. Links to the support portal are available in the Qdrant Cloud Console.
qdrant-landing/content/documentation/cloud/authentication.md

---
title: Authentication
weight: 30
---

# Authentication

This page shows you how to use the Qdrant Cloud Console to create a custom API key for a cluster. You will learn how to connect to your cluster using the new API key.

## Create API keys

The API key is only shown once after creation. If you lose it, you will need to create a new one. 
However, we recommend rotating the keys from time to time. To create additional API keys do the following.

1. Go to the [Cloud Dashboard](https://qdrant.to/cloud).
2. Select **Access Management** to display available API keys.
3. Click **Create** and choose a cluster name from the dropdown menu.
> **Note:** You can create a key that provides access to multiple clusters. Select desired clusters in the dropdown box.
4. Click **OK** and retrieve your API key. 

## Authenticate via SDK

Now that you have created your first cluster and key, you might want to access Qdrant Cloud from within your application.
Our official Qdrant clients for Python, TypeScript, Go, Rust, .NET and Java all support the API key parameter. 

```bash
curl \
  -X GET https://xyz-example.eu-central.aws.cloud.qdrant.io:6333 \
  --header 'api-key: <provide-your-own-key>'

# Alternatively, you can use the `Authorization` header with the `Bearer` prefix
curl \
  -X GET https://xyz-example.eu-central.aws.cloud.qdrant.io:6333 \
  --header 'Authorization: Bearer <provide-your-own-key>'
```

```python
from qdrant_client import QdrantClient

qdrant_client = QdrantClient(
    "xyz-example.eu-central.aws.cloud.qdrant.io",
    api_key="<paste-your-api-key-here>",
)
```

```typescript
import { QdrantClient } from "@qdrant/js-client-rest";

const client = new QdrantClient({
  host: "xyz-example.eu-central.aws.cloud.qdrant.io",
  apiKey: "<paste-your-api-key-here>",
});
```

```rust
use qdrant_client::client::QdrantClient;

let client = QdrantClient::from_url("xyz-example.eu-central.aws.cloud.qdrant.io:6334")
    .with_api_key("<paste-your-api-key-here>")
    .build()
    .unwrap();
```

```java
import io.qdrant.client.QdrantClient;
import io.qdrant.client.QdrantGrpcClient;

QdrantClient client =
    new QdrantClient(
        QdrantGrpcClient.newBuilder(
                "xyz-example.eu-central.aws.cloud.qdrant.io",
                6334,
                true)
            .withApiKey("<paste-your-api-key-here>")
            .build());
```

```csharp
using Qdrant.Client;

var client = new QdrantClient(
  host: "xyz-example.eu-central.aws.cloud.qdrant.io",
  https: true,
  apiKey: "<paste-your-api-key-here>"
);
```
qdrant-landing/content/documentation/cloud/aws-marketplace.md

---
title: AWS Marketplace
weight: 60
---

# Qdrant Cloud on AWS Marketplace

## Overview

Our [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-rtphb42tydtzg) listing streamlines access to Qdrant for users who rely on Amazon Web Services for hosting and application development. Please note that, while Qdrant's clusters run on AWS, you will still use the Qdrant Cloud infrastructure. 

## Billing

You don't need to use a credit card to sign up for Qdrant Cloud. Instead, all billing is processed through the AWS Marketplace and the usage of Qdrant is added to your existing billing for AWS services. It is common for AWS to abstract usage based pricing in the AWS marketplace, as there are too many factors to model when calculating billing from the AWS side. 

![pricing](/docs/cloud/pricing.png)

The payment is carried out via your AWS Account. To get a clearer idea for the pricing structure, please use our [Billing Calculator](https://cloud.qdrant.io/calculator).

## How to subscribe

1. Go to [Qdrant's AWS Marketplace listing](https://aws.amazon.com/marketplace/pp/prodview-rtphb42tydtzg).
2. Click the bright orange button - **View purchase options**. 
3. On the next screen, under Purchase, click **Subscribe**.
4. Up top, on the green banner, click **Set up your account**.
![setup](/docs/cloud/setup.png)

You will be transferred outside of AWS to [Qdrant Cloud](https://qdrant.to/cloud) via your unique AWS Offer ID. 

The Billing Details screen will open in Qdrant Cloud Console. Stay in this console if you want to create your first Qdrant Cluster hosted on AWS.

> **Note:** You do not have to return to the AWS Control Panel. All Qdrant infrastructure is provisioned from the Qdrant Cloud Console. 

## Next steps

Now that you have signed up via AWS Marketplace, please read our instructions to get started:

1. Learn more about [cluster creation and basic config](../../cloud/create-cluster/) in Qdrant Cloud.

2. Learn how to [authenticate and access your cluster](../../cloud/authentication/).

3. Additional open source [documentation](/documentation/guides/common-errors/).
qdrant-landing/content/documentation/cloud/cluster-scaling.md

---
title: Cluster scaling
weight: 50
---

# Cluster scaling

The amount of data is always growing and at some point you might need to upgrade the capacity of your cluster.
There are different options for how it can be done.

## Vertical scaling

Vertical scaling, also known as vertical expansion, is the process of increasing the capacity of a cluster by adding more resources, such as memory, storage, or processing power.

You can start with a minimal cluster configuration of 2GB of RAM and resize it up to 64GB of RAM (or even more if desired) over the time step by step with the growing amount of data in your application.
If your cluster consists of several nodes each node will need to be scaled to the same size.
Please note that vertical cluster scaling will require a short downtime period to restart your cluster.
In order to avoid a downtime you can make use of data replication, which can be configured on the collection level.
Vertical scaling can be initiated on the cluster detail page via the button "scale up".

## Horizontal scaling

Vertical scaling can be an effective way to improve the performance of a cluster and extend the capacity, but it has some limitations.
The main disadvantage of vertical scaling is that there are limits to how much a cluster can be expanded.
At some point, adding more resources to a cluster can become impractical or cost-prohibitive.
In such cases, horizontal scaling may be a more effective solution.
Horizontal scaling, also known as horizontal expansion, is the process of increasing the capacity of a cluster by adding more nodes and distributing the load and data among them. 
The horizontal scaling at Qdrant starts on the collection level.
You have to choose the number of shards you want to distribute your collection around while creating the collection.
Please refer to the [sharding documentation](../../guides/distributed_deployment/#sharding) section for details.


Important: The number of shards means the maximum amount of nodes you can add to your cluster. In the beginning, all the shards can reside on one node.
With the growing amount of data you can add nodes to your cluster and move shards to the dedicated nodes using the [cluster setup API](../../guides/distributed_deployment/#cluster-scaling). 

We will be glad to consult you on an optimal strategy for scaling.
[Let us know](mailto:cloud@qdrant.io) your needs and decide together on a proper solution. We plan to introduce an auto-scaling functionality. Since it is one of most desired features, it has a high priority on our Cloud roadmap.
qdrant-landing/content/documentation/cloud/create-cluster.md

---
title: Create a cluster
weight: 20
---

# Create a cluster

This page shows you how to use the Qdrant Cloud Console to create a custom Qdrant Cloud cluster.

> **Prerequisite:** Please make sure you have provided billing information before creating a custom cluster. 

1. Start in the **Clusters** section of the [Cloud Dashboard](https://cloud.qdrant.io/). 
1. Select **Clusters** and then click **+ Create**.
1. In the **Create a cluster** screen select **Free** or **Standard**
   For more information on a free cluster, see the [Cloud quickstart](/documentation/cloud/quickstart-cloud/). The remaining steps assume you want a standard cluster.
1. Select a provider. Currently, you can deploy to:

   - Amazon Web Services (AWS)
   - Google Cloud Platform (GCP)
   - Microsoft Azure 

1. Choose your data center region. If you have latency concerns or other topology-related requirements, [**let us know**](mailto:cloud@qdrant.io).
1. Configure RAM for each node (2 GB to 64 GB). 
   >  For more information, see our [**Capacity and Sizing**](/documentation/cloud/capacity-sizing/) guidance. If you need more capacity per node, [**let us know**](mailto:cloud@qdrant.io).
1. Choose the number of vCPUs per node (0.5 core to 16 cores). If you add more
   RAM, the menu provides different options for vCPUs.
1. Select the number of nodes you want the cluster to be deployed on. 

   > Each node is automatically attached with a disk space offering enough space for your data if you decide to put the metadata or even the index on the disk storage.
1. Select the disk space for your deployment. You can choose from 8 GB to 2 TB.
1. Review your cluster configuration and pricing.
1. When you're ready, select **Create**. It takes some time to provision your cluster.

Once provisioned, you can access your cluster on ports 443 and 6333 (REST)
and 6334 (gRPC).

![Cluster configured in the UI](/docs/cloud/create-cluster-test.png)

You should now see the new cluster in the **Clusters** menu.

A custom cluster includes the following resources. The values in the table are maximums.

| Resource   | Value (max) |
|------------|-------------|
| RAM        | 64 GB       |
| vCPU       | 16 vCPU     |
| Disk space | 2 TB        |
| Nodes      | 10          |  

### Included features (paid)

The features included with this cluster are:

- Dedicated resources
- Backup and disaster recovery
- Horizontal and vertical scaling
- Monitoring and log management

Learn more about these features in the [Qdrant Cloud dashboard](https://cloud.qdrant.io/).

## Next steps

You will need to connect to your new Qdrant Cloud cluster. Follow [**Authentication**](/documentation/cloud/authentication/) to create one or more API keys. 

Your new cluster is highly available and responsive to your application requirements and resource load. Read more in [**Cluster Scaling**](/documentation/cloud/cluster-scaling/).
qdrant-landing/content/documentation/cloud/gcp-marketplace.md

---
title: GCP Marketplace
weight: 60
---

# Qdrant Cloud on GCP Marketplace

Our [GCP Marketplace](https://console.cloud.google.com/marketplace/product/qdrant-public/qdrant)
listing streamlines access to Qdrant for users who rely on the Google Cloud Platform for
hosting and application development. While Qdrant's clusters run on GCP, you are using the
Qdrant Cloud infrastructure. 

## Billing

You don't need a credit card to sign up for Qdrant Cloud. Instead, all billing is
processed through the GCP Marketplace. Usage is added to your existing billing
for GCP.

Payment is made through your GCP Account. Our [Billing Calculator](https://cloud.qdrant.io/calculator)
can provide more information about costs.

Costs from cloud providers are based on usage. You can subscribe to Qdrant on
the GCP Marketplace without paying more.

## How to subscribe

1. Go to the [GCP Marketplace listing for Qdrant](https://console.cloud.google.com/marketplace/product/qdrant-public/qdrant).
1. Select **Subscribe**. (If you have already subscribed, select
   **Manage on Provider**.)
1. On the next screen, choose options as required, and select **Subscribe**.
1. On the pop-up window that appers, select **Sign up with Qdrant**.

GCP transfers you to the [Qdrant Cloud](https://cloud.qdrant.io/).

The Billing Details screen opens in the Qdrant Cloud Console. If you do not
already see a menu, select the "hamburger" icon (with three short horizontal
lines) in the upper-left corner of the window.

> **Note:** You do not have to return to GCP. All Qdrant infrastructure is provisioned from the Qdrant Cloud Console. 

## Next steps

Now that you have signed up through GCP, please read our instructions to get started:

1. Learn more about how you can [Create a cluster](/documentation/cloud/create-cluster/).
1. Learn how to [Authenticate](/documentation/cloud/authentication/) and access your cluster.
qdrant-landing/content/documentation/cloud/quickstart-cloud.md

---
title: Cloud Quickstart
weight: 10
aliases:
  - ../cloud-quick-start
  - cloud-quick-start
---

# Cloud Quickstart
This page shows you how to use the Qdrant Cloud Console to create a free tier cluster and then connect to it with Qdrant Client. 

## Create a Free Tier cluster

1. Start in the **Overview** section of the [Cloud Dashboard](https://cloud.qdrant.io/). 
1. Find the dashboard menu in the left-hand pane. If you do not see it, select
   the icon with three horizonal lines in the upper-left of the screen
1. Select **Clusters**. On the Clusters page, select **Create**.
1. In the **Create a Cluster** page, select **Free**
1. Scroll down. Confirm your cluster configuration, and select **Create**.

You should now see your new free tier cluster in the **Clusters** menu.

A free tier cluster includes the following resources:

| Resource   | Value |
|------------|-------|
| RAM        | 1 GB  |
| vCPU       | 0.5   |
| Disk space | 4 GB  |
| Nodes      | 1     |

## Get an API key

To use your cluster, you need an API key. Read our documentation on [Cloud
Authentication](/documentation/cloud/authentication/) for the process. 

## Test cluster access

After creation, you will receive a code snippet to access your cluster. Your generated request should look very similar to this one:

```bash
curl \
  -X GET 'https://xyz-example.eu-central.aws.cloud.qdrant.io:6333' \
  --header 'api-key: <paste-your-api-key-here>'
```
Open Terminal and run the request. You should get a response that looks like this:

```bash
{"title":"qdrant - vector search engine","version":"1.8.1"}
```

> **Note:** You need to include the API key in the request header for every
> request over REST or gRPC.

## Authenticate via SDK

Now that you have created your first cluster and API key, you can access the
Qdrant Cloud from within your application.
Our official Qdrant clients for Python, TypeScript, Go, Rust, and .NET all
support the API key parameter. 

```python
from qdrant_client import QdrantClient

qdrant_client = QdrantClient(
    "xyz-example.eu-central.aws.cloud.qdrant.io",
    api_key="<paste-your-api-key-here>",
)
```

```typescript
import { QdrantClient } from "@qdrant/js-client-rest";

const client = new QdrantClient({
  host: "xyz-example.eu-central.aws.cloud.qdrant.io",
  apiKey: "<paste-your-api-key-here>",
});
```

```rust
use qdrant_client::client::QdrantClient;

let client = QdrantClient::from_url("xyz-example.eu-central.aws.cloud.qdrant.io:6334")
    .with_api_key("<paste-your-api-key-here>")
    .build()
    .unwrap();
```

```java
import io.qdrant.client.QdrantClient;
import io.qdrant.client.QdrantGrpcClient;

QdrantClient client =
    new QdrantClient(
        QdrantGrpcClient.newBuilder(
                "xyz-example.eu-central.aws.cloud.qdrant.io",
                6334,
                true)
            .withApiKey("<paste-your-api-key-here>")
            .build());
```

```csharp
using Qdrant.Client;

var client = new QdrantClient(
  host: "xyz-example.eu-central.aws.cloud.qdrant.io",
  https: true,
  apiKey: "<paste-your-api-key-here>"
);
```
qdrant-landing/content/documentation/concepts/_index.md

---
title: Concepts
weight: 21
# If the index.md file is empty, the link to the section will be hidden from the sidebar
---

# Concepts

Think of these concepts as a glossary. Each of these concepts include a link to
detailed information, usually with examples. If you're new to AI, these concepts
can help you learn more about AI and the Qdrant approach.

## Collections

[Collections](/documentation/concepts/collections/) define a named set of points that you can use for your search.

## Payload

A [Payload](/documentation/concepts/payload/) describes information that you can store with vectors.

## Points

[Points](/documentation/concepts/points/) are a record which consists of a vector and an optional payload. 

## Search

[Search](/documentation/concepts/search/) describes _similarity search_, which set up related objects close to each other in vector space.

## Explore

[Explore](/documentation/concepts/explore/) includes several APIs for exploring data in your collections.

## Filtering

[Filtering](/documentation/concepts/filtering/) defines various database-style clauses, conditions, and more.

## Optimizer

[Optimizer](/documentation/concepts/optimizer/) describes options to rebuild
database structures for faster search. They include a vacuum, a merge, and an
indexing optimizer.

## Storage

[Storage](/documentation/concepts/storage/) describes the configuration of storage in segments, which include indexes and an ID mapper.

## Indexing

[Indexing](/documentation/concepts/indexing/) lists and describes available indexes. They include payload, vector, sparse vector, and a filterable index.

## Snapshots

[Snapshots](/documentation/concepts/snapshots/) describe the backup/restore process (and more) for each node at specific times.
qdrant-landing/content/documentation/embeddings/_index.md

---
title: Embeddings
weight: 34
---

| Embeddings Providers          |
| ----------------------------- |
| [Aleph Alpha](./aleph-alpha/) |
| [Bedrock](./bedrock/)         |
| [Cohere](./cohere/)           |
| [Gemini](./gemini/)           |
| [Jina](./jina-emebddngs/)     |
| [Mistral](./mistral/)         |
| [Nomic](./nomic/)             |
| [Nvidia](./nvidia/)           |
| [OpenAI](./openai/)           |
| [Prem AI](./premai/)          |
| [Snowflake](./snowflake/)     |
| [Upstage](./upstage/)        |
| [Voyage AI](./voyage/)        |