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"Create a Neural Search Service with Fastembed"
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"Create a Neural Search Service with Fastembed"
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[
"What is a Vector Database? - Qdrant"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(1) > li:nth-of-type(1) | [
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[
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"Why use a Vector Database?"
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] | p | You can see how scaling to millions of vectors can demand substantial system memory and computational resources. | [
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[
"What is a Vector Database? - Qdrant",
"Why use a Vector Database?"
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[
"What is a Vector Database? - Qdrant",
"Why use a Vector Database?"
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[
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"What is Vector Data?"
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[
"What is a Vector Database? - Qdrant",
"What is Vector Data?"
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"What is a Vector Database? - Qdrant",
"What is Vector Data?"
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"articles/what-is-a-vector-database"
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[
"What is a Vector Database? - Qdrant",
"What is Vector Data?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15) | [
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"articles",
"articles/what-is-a-vector-database"
] | 534 |
[
"What is a Vector Database? - Qdrant",
"What is Vector Data?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16) | [
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] | p | So from now on, when we talk about high-dimensional data, we mean that the data contains a large number of data points (pixels, features, semantics, syntax). | [
"articles",
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[
"What is a Vector Database? - Qdrant",
"What is Vector Data?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17) | [
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[
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"How do Embeddings Work?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(22) | [
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"articles",
"articles/what-is-a-vector-database"
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[
"What is a Vector Database? - Qdrant"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(2) | [
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"What is a Vector Database? - Qdrant",
"What is Indexing?"
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[
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"What is Indexing?"
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[
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"What is Binary Quantization?"
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[
"What is a Vector Database? - Qdrant",
"What is Similarity Search?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(36) | [
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"articles/what-is-a-vector-database"
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[
"What is a Vector Database? - Qdrant",
"What is Similarity Search?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(36) | [
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[
"What is a Vector Database? - Qdrant",
"What is Similarity Search?"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(37) | [
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[
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[
"What is a Vector Database? - Qdrant",
"What is Similarity Search?"
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[
"What is a Vector Database? - Qdrant"
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] | p | For example, in a database containing text documents, a user might want to search for documents not only based on textual similarity but also filter the results by publication date or author. | [
"articles",
"articles/what-is-a-vector-database"
] | 588 |
[
"What is a Vector Database? - Qdrant",
"Using Metadata and Filters"
] | /articles/what-is-a-vector-database/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(46) | [
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"Using Metadata and Filters"
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"Using Metadata and Filters"
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[
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[
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"Data Security and Access Control"
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Subsets and Splits