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Commit b443583

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docs: add benchmark reference to feature summary (#510)
* docs: add benchmark reference to feature summary add link to the benchmark so that users can quickly choose the right database storage to use Co-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>
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‎docs/advanced/document-store/index.md‎

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@@ -151,15 +151,19 @@ Using dataclass gives you better type-checking in IDE but requires an extra impo
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DocArray supports multiple storage backends with different search features. The following table showcases relevant functionalities that are supported (✅) or not supported (❌) in DocArray depending on the backend:
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| Name | Construction | vector search | vector search + filter | filter|
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|--------------------------------------|------------------------------------------|---------------|------------------------|---------------|
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| In memory | `DocumentArray()` ||||
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| [`Sqlite`](./sqlite.md) | `DocumentArray(storage='sqlite')` ||||
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| [`Weaviate`](./weaviate.md) | `DocumentArray(storage='weaviate')` ||||
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| [`Qdrant`](./qdrant.md) | `DocumentArray(storage='qdrant')` ||||
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| [`Annlite`](./annlite.md) | `DocumentArray(storage='annlite')` ||||
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| [`ElasticSearch`](./elasticsearch.md) | `DocumentArray(storage='elasticsearch')` ||||
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| [`Redis`](./redis.md) | `DocumentArray(storage='redis')` ||||
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| Name | Construction | vector search | vector search + filter | filter |
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|---------------------------------------|------------------------------------------|----------------|------------------------|---------------|
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| In memory | `DocumentArray()` ||||
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| [`Sqlite`](./sqlite.md) | `DocumentArray(storage='sqlite')` ||||
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| [`Weaviate`](./weaviate.md) | `DocumentArray(storage='weaviate')` ||||
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| [`Qdrant`](./qdrant.md) | `DocumentArray(storage='qdrant')` ||||
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| [`AnnLite`](./annlite.md) | `DocumentArray(storage='annlite')` ||||
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| [`ElasticSearch`](./elasticsearch.md) | `DocumentArray(storage='elasticsearch')` ||||
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| [`Redis`](./redis.md) | `DocumentArray(storage='redis')` ||||
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The right backend choice depends on the scale of your data, the required performance and the desired ease of setup. For most use cases we recommend starting with [`AnnLite`](./annlite.md).
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[**Check our One Million Scale Benchmark for more details**](./benchmark#conclusion).
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- **filter**: perform a filter step over the data. The input of the search function is a filter.
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The capabilities of **vector search**, **vector search + filter** can be used using the {meth}`~docarray.array.mixins.find.FindMixin.find` or {func}`~docarray.array.mixins.match.MatchMixin.match` methods thorugh a `DocumentArray`.
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The capabilities of **vector search**, **vector search + filter** can be used using the {meth}`~docarray.array.mixins.find.FindMixin.find` or {func}`~docarray.array.mixins.match.MatchMixin.match` methods through a `DocumentArray`.
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The **filter** functionality is available using the `.find` method in a `DocumentArray`.
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A detailed explanation of the differences between `.find` and `.match` can be found [`here`](./../../../fundamentals/documentarray/matching)
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A detailed explanation of the differences between `.find` and `.match` can be found [here](./../../../fundamentals/documentarray/matching)
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### Vector search example
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