Milvus vs. voyage-code-3 Comparison


Milvus Zilliz	voyage-code-3 MongoDB	+	+
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About Vector database built for scalable similarity search. Open-source, highly scalable, and blazing fast. Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. With Milvus vector database, you can create a large-scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large-scale vector data. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage.	About Voyage AI introduces voyage-code-3, a next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average of 13.80% and 16.81% on a suite of 32 code retrieval datasets, respectively. It supports embeddings of 2048, 1024, 512, and 256 dimensions and offers multiple embedding quantization options, including float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a 32 K-token context length, it surpasses OpenAI's 8K and CodeSage Large's 1K context lengths. Voyage-code-3 employs Matryoshka learning to create embeddings with a nested family of various lengths within a single vector. This allows users to vectorize documents into a 2048-dimensional vector and later use shorter versions (e.g., 256, 512, or 1024 dimensions) without re-invoking the embedding model.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Enterprises in need of a solution to manage their vector data and create a large scale similarity search service	Audience AI researchers and developers in search of a solution providing an embedding model for code retrieval
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing No information available. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Supported In Person Supported	Training Documentation Supported Webinars Not Supported Live Online Supported In Person Not Supported
Company Information Zilliz Founded: 2020 United States milvus.io	Company Information MongoDB Founded: 2007 United States blog.voyageai.com/2024/12/04/voyage-code-3/
Alternatives Qdrant	Alternatives voyage-3-large MongoDB
Zilliz Cloud Zilliz	Cohere Embed Cohere
Chroma	Voyage AI MongoDB
LanceDB	voyage-4-large Voyage AI
Pinecone View All	Codestral Embed Mistral AI View All
Categories Context Engineering Supported Database Supported Vector Databases Supported	Categories Embedding Models Supported

Integrations Amazon S3 Supported Apache Kafka Supported Apache Pulsar Supported Azure Blob Storage Supported Cognee Supported Database Mart Supported Docker Supported Elasticsearch Not Supported IBM watsonx.data Supported Kubernetes Supported Milvus Not Supported MinIO Supported Prompt Security Supported Qdrant Not Supported Vespa Not Supported Zilliz Cloud Supported Show More Integrations View All 12 Integrations	Integrations Amazon S3 Not Supported Apache Kafka Not Supported Apache Pulsar Not Supported Azure Blob Storage Not Supported Cognee Not Supported Database Mart Not Supported Docker Not Supported Elasticsearch Supported IBM watsonx.data Not Supported Kubernetes Not Supported Milvus Supported MinIO Not Supported Prompt Security Not Supported Qdrant Supported Vespa Supported Zilliz Cloud Not Supported Show More Integrations View All 4 Integrations
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