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‎docs/tools/vdb_table/data/apachedoris.json‎

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{
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"name": "Apache Doris",
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"links": {
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"docs": "https://doris.apache.org/docs/dev/ai/vector-search/",
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"github": "https://github.com/apache/doris",
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"website": "https://doris.apache.org/",
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"vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/575",
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"poc_github": "https://github.com/zhiqiang-hhhh",
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"slug": "Fastest Search & Analytics in One Unified System"
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},
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"oss": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/compute-storage-decoupled/overview/",
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"comment": ""
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},
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"license": {
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"value": "Apache 2.0",
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"source_url": "",
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"comment": ""
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},
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"dev_languages": {
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"value": [
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"java",
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"c++"
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],
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"source_url": "https://github.com/apache/doris",
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"comment": ""
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},
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"vector_launch_year": 2025,
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"metadata_filter": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/ai/text-search/overview/",
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"comment": ""
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},
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"hybrid_search": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/ai/vector-search#ann-search-with-additional-filters",
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"comment": ""
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},
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"facets": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/ai/vector-search#approximate-range-search",
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"comment": "Doris has full support for SQL. You can use standard SQL syntax to perform faceted search on vector data."
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},
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"geo_search": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/sql-manual/basic-element/sql-data-types/semi-structured/GEO",
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"comment": ""
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},
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"multi_vec": {
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"support": "full",
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"source_url": "",
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"comment": "You can create a teble with multiple vector columns to store different types of vectors."
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},
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"sparse_vectors": {
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"support": "none",
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"source_url": "",
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"comment": ""
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},
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"bm25": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/ai/text-search/scoring",
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"comment": ""
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},
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"full_text": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/dev/ai/text-search/search-operators",
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"comment": ""
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},
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"embeddings_text": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/4.x/sql-manual/sql-functions/ai-functions/distance-functions/embed/",
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"comment": "You can convert text to embeddings using built-in AI functions."
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},
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"embeddings_image": {
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"support": "",
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"source_url": "",
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"comment": ""
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},
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"embeddings_structured": {
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"support": "",
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"source_url": "",
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"comment": ""
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},
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"rag": {
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"support": "",
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"source_url": "",
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"comment": ""
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},
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"recsys": {
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"support": "",
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"source_url": "",
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"comment": ""
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},
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"langchain": {
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"support": "full",
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"source_url": "",
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"comment": ""
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},
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"llamaindex": {
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"support": "full",
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"source_url": "",
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"comment": ""
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},
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"managed_cloud": {
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"support": "full",
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"source_url": "",
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"comment": ""
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},
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"pricing": {
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"value": "",
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"source_url": "",
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"comment": ""
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},
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"in_process": {
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"support": "none",
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"source_url": "",
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"comment": ""
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},
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"multi_tenancy": {
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"support": "full",
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"source_url": "https://doris.apache.org/blog/multi-tenant-workload-isolation-in-apache-doris/",
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"comment": ""
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},
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"disk_index": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/4.x/ai/vector-search#approximate-nearest-neighbor-search",
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"comment": "Via Faiss"
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},
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"ephemeral": {
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"support": "none",
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"source_url": "",
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"comment": ""
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},
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"sharding": {
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"support": "full",
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"source_url": "",
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"comment": "Support partitioning and sharding for tables with vector columns"
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},
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"doc_size": {
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"bytes": 0,
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"unlimited": true,
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"source_url": "",
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"comment": ""
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},
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"vector_dims": {
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"value": 0,
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"unlimited": true,
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"source_url": "",
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"comment": ""
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},
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"int8_quantization": {
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"support": "full",
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"source_url": "https://doris.apache.org/docs/4.x/ai/vector-search#vector-quantization",
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"comment": ""
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},
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"index_types": {
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"value": [
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"HNSW",
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"IVF",
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"FLAT"
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],
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"source_url": "https://doris.apache.org/docs/4.x/ai/vector-search#approximate-nearest-neighbor-search",
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"comment": "via Faiss"
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},
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"github_stars": {
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"value": 14600,
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"source_url": "https://github.com/ClickHouse/ClickHouse",
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"comment": "",
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"value_90_days": 0
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},
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"docker_pulls": {
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"value": 0,
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"source_url": "",
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"comment": "",
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"value_90_days": 0
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},
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"pypi_downloads": {
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"value": 0,
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"source_url": "",
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"comment": "",
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"value_90_days": 0
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},
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"npm_downloads": {
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"value": 0,
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"source_url": "",
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"comment": "",
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"value_90_days": 0
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},
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"crates_io_downloads": {
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"value": 0,
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"source_url": "",
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"comment": "",
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"value_90_days": 0
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}
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}

‎docs/tools/vdb_table/data/couchbase.json‎

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},
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"oss": {
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"support": "partial",
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"source_url": "https://www.couchbase.com/blog/couchbase-adopts-bsl-license/",
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"comment": "Vector search currently only part of Enterprise and DBaaS editions"
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"source_url": "https://github.com/blevesearch/bleve",
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"comment": "Hybrid Vector uses Bleve and is OSS, Hyperscale & Composite currently only part of Enterprise and DBaaS editions"
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},
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"license": {
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"value": "Proprietary",
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"source_url": "https://www.couchbase.com/blog/couchbase-adopts-bsl-license/",
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"comment": "Vector search currently only part of Enterprise and DBaaS editions"
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"comment": "Hyperscale & Composite currently only part of Enterprise and DBaaS editions"
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},
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"dev_languages": {
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"value": [
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"c++",
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"erlang"
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],
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"source_url": "",
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"comment": ""
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"source_url": "https://github.com/couchbase/manifest",
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"comment": "Couchbase is developed with a variety of languages, and it varies by component."
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},
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"vector_launch_year": 2024,
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"metadata_filter": {
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"source_url": "https://docs.couchbase.com/cloud/vector-search/create-vector-search-index-ui.html",
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"comment": ""
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},
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"bm25": {
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"support": "full",
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"source_url": "https://docs.couchbase.com/cloud/search/run-searches.html#bm25",
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"comment": ""
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},
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"full_text": {
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"support": "full",
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"source_url": "https://docs.couchbase.com/c-sdk/current/concept-docs/full-text-search-overview.html",
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"comment": ""
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},
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"embeddings_text": {
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"support": "none",
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"source_url": "",
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"comment": ""
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"support": "full",
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"source_url": "https://docs.couchbase.com/ai/build/model-service/deploy-embed-model.html",
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"comment": "Capella AI Services can host text embedding models"
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},
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"embeddings_image": {
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"support": "none",
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"comment": ""
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},
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"rag": {
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"support": "none",
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"source_url": "",
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"comment": ""
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"support": "full",
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"source_url": "https://docs.couchbase.com/ai/build/model-service/deploy-llm-model.html",
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"comment": "Capella AI Services can host LLM models"
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},
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"langchain": {
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"support": "full",
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"comment": ""
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},
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"ephemeral": {
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"support": "none",
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"source_url": "",
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"comment": ""
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"support": "full",
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"source_url": "https://docs.couchbase.com/server/current/indexes/storage-modes.html#memory-optimized-index-storage",
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"comment": "Memory-optimized indexes keep all the index data in memory"
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},
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"sharding": {
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"support": "full",
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"comment": ""
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},
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"int8_quantization": {
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"support": "partial",
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"source_url": "https://docs.couchbase.com/couchbase-lite/3.2/java/working-with-vector-search.html#create-a-vector-index",
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"comment": "Automatic algorithm selection between: IdMap2,Flat, IVF,Flat, IVF,SQ8"
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"support": "full",
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"source_url": "https://docs.couchbase.com/cloud/vector-search/vector-search-index-architecture.html#scalar-quant",
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"comment": "Supports int8 (and int4) scalar quantization to reduce vector index size"
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},
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"github_stars": {
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"value": 1662,
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"value_90_days": 0
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},
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"pypi_downloads": {
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"value": 22599014,
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"value": 22959614,
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"source_url": "https://pypi.org/project/couchbase/",
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"comment": "",
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"value_90_days": 3364928
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"comment": "Total downloads and previous 90 days from BigTable data for just the main Couchbase library",
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"value_90_days": 3364746
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},
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"npm_downloads": {
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"value": 1916327,

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