Performance tuning involves minimizing query latency and controlling costs.

Key techniques include pre‑aggregating common metrics, using materialized views, and implementing result caching at the analytics layer.

Many embedded platforms provide both session caches (per user) and shared caches (across users) to reduce database load.

You can also push down compute to your data warehouse and leverage cloud scaling features.

Monitoring query performance and adjusting concurrency limits helps ensure fairness across tenants.

MageMetrics employs a compounding ‘intent‑to‑SQL’ flywheel that learns which queries are popular and caches them, while still allowing fresh results when underlying data changes.