Multimodal AI Datastore
Views
Learn how to create and use virtual derived tables in Pixeltable through views
When to Use Views
Views in Pixeltable are best used when you need to:
- Transform Data: When you need to process or reshape data from a base table (e.g., splitting documents into chunks, extracting features from images)
- Filter Data: When you frequently need to work with a specific subset of your data
- Create Virtual Tables: When you want to avoid storing redundant data and automatically keep derived data in sync
- Build Data Workflows: When you need to chain multiple data transformations together
- Save Storage: When you want to compute data on demand rather than storing it permanently
Choose views over tables when your data is derived from other base tables and needs to stay synchronized with its source. Use regular tables when you need to store original data or when the computation cost of deriving data on demand is too high.
Phase 1: Define your base table and view structure
Phase 2: Use your application
View Types
View Operations
Query Operations
Query views like regular tables:
Computed Columns
Add computed columns to views:
Chaining Views
Create views based on other views:
Key Features
Automatic Updates
Views automatically update when base tables change
Virtual Storage
Views compute data on demand, saving storage
Workflow Integration
Views can be part of larger data workflows