Memory System

Arivu uses a scalable memory system to manage contextual session history across interactions.

Arivu ships with a robust and modular Memory System that provides context to the AI agents orchestrating Text-to-SQL logic. Memory allows Arivu to understand user references to prior messages, queries, or database tables.

Quick Storage Comparison

Feature Comparison

Feature	SQLite	Redis
Setup	Zero config	Requires server
Performance	Fast locally	Very fast (in-memory)
Deployment	Single machine	Distributed
Scaling	Limited	Excellent
Best for	Development	Production

Which Should I Use?

Start with SQLite

• Developing locally
• Testing Arivu
• Single-user applications
• Zero infrastructure overhead

Migrate to Redis

• Deploying to production
• Multiple workers/instances
• High performance needs
• Horizontal scaling required

Built-in Storage Backends

SQLite (Local)

File-based local persistent memory. Great for simple setups, local development, and small applications.

Redis (Remote)

In-memory data structure store. Optimized for distributed architectures, production deployments, and horizontal scaling.

Sessions & Threads

Memory in Arivu operates on the concept of Sessions (also known as threads). Every conversation is pinned to a unique session_id, meaning subsequent inputs within the same session will maintain context over table schemas, previously selected rows, and prior conversational turns automatically.