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Vector Databases: Pinecone, Weaviate & pgvector · Lesson

Weaviate Schema Definition

Design and manage your data schema in Weaviate, defining classes and properties for your vector objects.

Weaviate Schema: Your Data Map

Welcome to Weaviate! To store and search data effectively, Weaviate needs to understand its structure. This is where the schema comes in.

Think of a schema as a blueprint for your data. It defines the types of data you'll store and how they relate.

Why Schema Matters

A well-defined schema is crucial for:

  • Data Consistency: Ensuring all objects conform to expected types.
  • Efficient Indexing: Weaviate uses the schema to build efficient search indexes.
  • Vectorization: Guiding how Weaviate generates and stores vector embeddings for your data.
  • Querying: Enabling powerful semantic and filtered searches.

All lessons in this course

  1. Weaviate Schema Definition
  2. Importing Data Objects
  3. Weaviate GraphQL Queries
  4. Vectorizer Modules and Auto-Embedding
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