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Abdon Pijpelink
757767919b
* Change bulk upload from tutorial into guide * Add 'Mitigate Read-Write Contention' section to bulk upload guide * Update meta descriptions
48 lines
2.3 KiB
Markdown
48 lines
2.3 KiB
Markdown
---
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title: Manage Data
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short_description: "Structure, store, and organize data in Qdrant — points, vectors, payloads, collections, indexes, and quantization."
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description: "Manage data in Qdrant by configuring collections, points, payloads, vector indexes, and quantization to control how records are stored, indexed, and retrieved."
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weight: 205
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partition: develop
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---
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# Manage Data
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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.
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## Points
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[Points](/documentation/manage-data/points/) are the fundamental unit of data in Qdrant — each point is a record consisting of a vector and an optional payload.
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## Vectors
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[Vectors](/documentation/manage-data/vectors/) define how data is represented in vector space, including support for dense, sparse, and multivector configurations.
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## Payload
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A [Payload](/documentation/manage-data/payload/) is structured metadata you can attach to a point, enabling filtering and enriched search results.
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## Collections
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[Collections](/documentation/manage-data/collections/) are named groups of points that share the same vector configuration and serve as the top-level organizational unit in Qdrant.
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## Storage
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[Storage](/documentation/manage-data/storage/) describes how Qdrant persists vector and payload data, including segment structure and in-memory vs. on-disk options.
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## Indexing
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[Indexing](/documentation/manage-data/indexing/) covers the available index types — payload, vector, sparse, and filterable — and how they accelerate search and filtering.
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## Quantization
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[Quantization](/documentation/manage-data/quantization/) reduces memory usage by compressing vectors, with options for scalar, product, and binary quantization.
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## Multitenancy
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[Multitenancy](/documentation/manage-data/multitenancy/) explains strategies for isolating data across multiple users or tenants within a single Qdrant deployment.
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## Bulk Upload
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[Bulk Upload](/documentation/manage-data/bulk-upload/) covers strategies for ingesting large datasets efficiently, including batching, parallelization, and index configuration.
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