# Manage Data
# Manage Data

Learn how to structure, store, and organize your data in Qdrant. These pages cover the core building blocks — from individual records and the vectors that represent them, to collections, payloads, and the indexing and quantization options that control how data is stored and retrieved.

## Points

[Points](/documentation/manage-data/points/index.md) are the fundamental unit of data in Qdrant — each point is a record consisting of a vector and an optional payload.

## Vectors

[Vectors](/documentation/manage-data/vectors/index.md) define how data is represented in vector space, including support for dense, sparse, and multivector configurations.

## Payload

A [Payload](/documentation/manage-data/payload/index.md) is structured metadata you can attach to a point, enabling filtering and enriched search results.

## Collections

[Collections](/documentation/manage-data/collections/index.md) are named groups of points that share the same vector configuration and serve as the top-level organizational unit in Qdrant.

## Storage

[Storage](/documentation/manage-data/storage/index.md) describes how Qdrant persists vector and payload data, including segment structure and in-memory vs. on-disk options.

## Indexing

[Indexing](/documentation/manage-data/indexing/index.md) covers the available index types — payload, vector, sparse, and filterable — and how they accelerate search and filtering.

## Quantization

[Quantization](/documentation/manage-data/quantization/index.md) reduces memory usage by compressing vectors, with options for scalar, product, and binary quantization.

## Multitenancy

[Multitenancy](/documentation/manage-data/multitenancy/index.md) explains strategies for isolating data across multiple users or tenants within a single Qdrant deployment.