Materialized views in PostgreSQL can be useful for caching query results, but they have limitations. They can become outdated quickly and require manual refreshes to keep them up-to-date. In contrast, continuous aggregates in TimescaleDB are designed to automatically update with new data, using a combination of views and materialized hypertables. This approach provides faster performance and more consistent results than traditional materialized views or normal views. However, it also requires careful configuration and management of the invalidation log to ensure that out-of-order modifications are handled correctly. Overall, continuous aggregates offer a powerful solution for time-series data analysis, but they require a nuanced understanding of their trade-offs and limitations.