EEnterpriseLLayerIIntelligence by Techbible
Resources

The AI database developers love - Database Management Tool

The AI database developers love

The AI database developers love

Bring AI-native applications to life with less hallucination, data leakage, and vendor lock-in

Cost

Free Tier

Rating

People love it

Time to value

Quick Setup (< 1 hour)

You can use Weaviate to build AI applications that search through unstructured data, create chatbots with retrieval augmented generation, and develop AI agents. It's a vector database that handles embeddings and similarity search automatically. You can connect your own machine learning models or use built-in embedding services. The database scales from small projects to billions of data points and can be deployed in the cloud or on-premises.

What The AI database developers love does

Import and vectorize unstructured data automaticallyQuery data using natural language instead of keywordsSet up hybrid search combining multiple search methodsConfigure multi-tenant databases for different usersConnect custom embedding models to the databaseScale database clusters based on traffic demandsMonitor database performance and query analyticsImplement real-time data ingestion pipelinesAutomatically generates embeddings for your dataSupports hybrid search combining vector and keyword searchBuilt-in multi-tenancy for isolating dataScales to billions of data objectsConnects to custom machine learning modelsGraphQL and REST API accessReal-time data updates and queryingEnterprise security with RBAC and compliance

Pricing breakdown

PlanPrice10 seats / yr
Cloud$0

Annual estimates assume continuous billing at the listed list price. Volume discounts typical above 50 seats.

Frequently asked

Want a tailored answer?

See whether The AI database developers love fits your stack.

Techbible weighs The AI database developers love against what you already pay for, your team shape, and the work that's actually happening. Free to start.

Weaviate, vector database, AI database, semantic search, retrieval augmented generation, RAG, AI agents, embeddings, unstructured data, machine learning, GraphQL, REST API, hybrid search, multi-tenant, scalable database, contextual search