ベクトルデータベース一覧

qdrant

Amazon Aurora: https://aws.amazon.com/blogs/database/leverage-pgvector-and-amazon-aurora-postgresql-for-natural-language-processing-chatbots-and-sentiment-analysis/

AnalyticDB for PostgreSQL: https://www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/4d5b34

AnnDB: https://anndb.com/

ArcadeDB: https://github.com/ArcadeData/arcadedb

Atlas: https://atlas.nomic.ai/

AwaDB: https://github.com/awa-ai/awadb

Azure Cognitive Search: https://azure.microsoft.com/en-us/products/ai-services/cognitive-search

BagelDB: https://www.bageldb.ai/

Cassandra: https://cwiki.apache.org/confluence/display/CASSANDRA/CEP-30%3A+Approximate+Nearest+Neighbor(ANN)+Vector+Search+via+Storage-Attached+Indexes

Chroma: https://www.trychroma.com/

Clarifai: https://www.clarifai.com/blog/finding-what-you-need-a-comprehensive-guide-to-vector-search

ClickHouse: https://clickhouse.com/

CloseVector: https://closevector-docs.getmegaportal.com/

CockroachDB: https://thenewstack.io/cockroach-labs-chief-targets-llms-with-vector-encoding/

CozoDB: https://docs.cozodb.org/en/latest/vector.html

DashVector: https://help.aliyun.com/document_detail/2510225.html

Databricks: https://www.databricks.com/company/newsroom/press-releases/databricks-introduces-new-generative-ai-tools-investing-lakehouse

DataStax Astra Vector Search: https://docs.datastax.com/en/astra-serverless/docs/vector-search/overview.html

DB5: https://vector5.ai/vector-database/

dingo: https://github.com/dingodb/dingo

deeplake: https://github.com/activeloopai/deeplake

DocArray Hsnwlib: https://docs.docarray.org/user_guide/storing/index_hnswlib/

DocArray In-Memory: https://docs.docarray.org/user_guide/storing/index_in_memory/

Elastic Search Relevance Engine (ESRE): https://www.elastic.co/enterprise-search/generative-ai

embeddinghub: https://github.com/featureform/featureform/tree/main/embeddinghub

Epsilla: https://github.com/epsilla-cloud/vectordb

Google Cloud AI: Vertex AI Matching Engine: https://cloud.google.com/vertex-ai/docs/matching-engine/overview

Google Cloud database systems: AlloyDB for PostgreSQL, Cloud SQL for PostgreSQL (based on pgvector)

Google Cloud AlloyDB AI: https://cloud.google.com/alloydb/ai

HyperVectorDB: https://github.com/deatos/HyperVectorDB

JaguarDB: http://www.jaguardb.com/

KDB.AI: https://kx.com/products/kdb-ai/

LanceDB: https://github.com/lancedb/lancedb

Lantern: https://github.com/lanterndata/lanterndb

Marqo: https://www.marqo.ai/

Meilisearch: https://www.meilisearch.com/

Metal: https://getmetal.io/ (it is noteworthy that their search in documents is based on prompting: https://docs.getmetal.io/introduction)

Milvus: https://milvus.io/

Milvus Lite: https://github.com/milvus-io/milvus-lite

MongoDB Atlas: https://www.mongodb.com/docs/atlas/atlas-search/field-types/knn-vector/

MyScale: https://myscale.com/

MySQL Heatwave: https://blogs.oracle.com/mysql/post/introducing-vector-store-and-generative-ai-in-mysql-heatwave

Neo4j: https://neo4j.com/generativeai/

NucliaDB: https://github.com/nuclia/nucliadb

OpenSearch: https://opensearch.org/platform/search/vector-database.html

Oracle 23c: https://docs.oracle.com/en/database/oracle/oracle-database/23/nfcoa/oracle-database-23c-new-features-guide.pdf

Orama: https://github.com/oramasearch/orama

Pinecone: https://www.pinecone.io/

pg_embedding: https://github.com/neondatabase/pg_embedding

pgvecto.rs: https://github.com/tensorchord/pgvecto.rs

Qdrant: https://qdrant.tech/

Qwak Vector Store: https://docs-saas.qwak.com/docs/vector-store

Redis: https://redis.io/docs/interact/search-and-query/search/vectors/

redisvl: https://github.com/RedisVentures/redisvl

RelevanceAI: https://documentation.relevanceai.com/datasets/introduction

Rockset: https://rockset.com/

ScaNN: https://github.com/google-research/google-research/tree/master/scann

scikit-learn: https://scikit-learn.org/stable/

SingleStore: https://www.singlestore.com/

sqlite-vss: https://github.com/asg017/sqlite-vss

StarRocks: https://www.starrocks.io/

supabase: https://supabase.com/

SuperDuperDB: https://github.com/SuperDuperDB/superduperdb

SWIFT Vector Database: https://github.com/Dripfarm/SVDB

Tair: https://www.alibabacloud.com/help/en/tair/product-overview/what-is-tair

Tencent Cloud VectorDB: https://technode.com/2023/07/05/tencent-cloud-unveils-ai-native-vector-database/

TerminusDB: https://terminusdb.com/vectorlink/

Tigris: https://www.tigrisdata.com/docs/quickstarts/quickstart-vector-search/

TileDB: https://tiledb.com/blog/why-tiledb-as-a-vector-database

Timescale Vector: https://www.timescale.com/blog/how-we-made-postgresql-the-best-vector-database/

tinyvector: https://github.com/m1guelpf/tinyvector

typesense: https://typesense.org/

txtai: https://github.com/neuml/txtai

Usearch: https://unum-cloud.github.io/usearch/

Vald: https://vald.vdaas.org/

vearch: https://github.com/vearch/vearch

vectara: https://vectara.com/

VectorDB: https://github.com/jina-ai/vectordb

Vectorize: https://developers.cloudflare.com/vectorize/

VectorLake: https://github.com/msoedov/vector_lake

vector-storage: https://github.com/nitaiaharoni1/vector-storage

vercel: https://vercel.com/ (via pgvector)

Vespa: https://vespa.ai/

victor: https://github.com/not-pizza/victor

vlite: https://github.com/sdan/vlite

Weaviate: https://weaviate.io/

Xata: https://xata.io/

Zep: https://www.getzep.com/

Zilliz: https://zilliz.com/