Weaviate Vector Database - Kubernetes Cluster
Weaviate
Product Overview
Weaviate is a popular open-source low-latency vector database with out-of-the-box support for multimodal media types (text, images, etc.). The database stores both objects and vectors, allowing for combining vector search with structured filtering and the fault tolerance of a cloud-native database. All are accessible through a wide variety of client-side programming languages.
Version: 1.20
By
Weaviate
Categories: Databases & Analytics Platforms
ML Solutions
Embeddings
Operating System
Linux
Delivery Methods
Container
Supported servicesAmazon ECSAmazon EKSAmazon ECS AnywhereAmazon EKS AnywhereSelf-managed Kubernetes
Highlights: End-to-end vector database for vector similarity search, hybrid search, and advanced filtered search. Optional integrations with SageMaker, Bedrock, OpenAI, Cohere, HuggingFace, and many others. Suited for vector search, retrieval augmented generation (RAG), and generative search.
Category: Infrastructure Software
Delivery Method: Container
Company Information
Company Name: Weaviate
About Company: Weaviate is an AI-native vector database. It allows you to store data objects and vector embeddings from your favorite ML models, and scale seamlessly into billions of data objects.