Weaviate
49 reviews
- 1 profiles
- 2 categories
Average star rating
4.4
Serving customers since
2019
Weaviate Reviews
MO
Muhammad O.
Salesforce Business Analyst | CRM & Sales Operations SpecialistWeaviate Makes Vector Search and Embeddings Simple
What I like most about Weaviate is how straightforward it makes working with vector search and embeddings. The setup feels intuitive, and it’s easy to store, search, and retrieve relevant data for AI applications without adding unnecessary complexity to my workflow.
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Nirmal K.
Content Manager @ Extramarks Education India Pvt. Ltd.Gold-Standard Hybrid Search for Highly Accurate RAG Retrieval
It natively supports hybrid search, allowing developers to combine dense vector search (for semantic meaning) with traditional keyword search (BM25). This is widely considered the gold standard for retrieving highly accurate context in RAG applications.
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Harshul S.
IT & Networking Professional | Cybersecurity & Firewall Specialist | Expert in Networking, System Administration & Technical Support | CompTIA Security+ | JNCIA-Junos CertifiedEasy, Scalable Vector Search with Solid Performance
What I like best about Weaviate is how easy it makes working with vector search at scale. The setup is straightforward, the performance is solid, and it handles embeddings without forcing you into complicated configurations. It feels like a tool built to get real semantic search running quickly.
About
What is Weaviate?
Weaviate is an open-source, AI-native vector database for building semantic search, hybrid search, RAG, and agentic AI applications. It stores data objects alongside vector embeddings and integrates with leading embedding and LLM providers. Weaviate is available self-hosted or as a fully managed service (Weaviate Cloud) on AWS, Google Cloud, and Azure, with a free tier, Query Agent for natural-language querying, and Engram for AI-agent memory. SOC 2 Type II certified, with HIPAA available.
Details
Year Founded
2019
Website
weaviate.io