![]() ![]() “Continuous aggregates may help with the management and analytics of time-series data in PostgreSQL, but that’s what NoSQL databases are for-they already provide the features you needed from the get-go. What About Other Databases?īy now, some readers might be thinking something along these lines: With this feature, managing and analyzing massive volumes of time-series data in PostgreSQL finally felt fast and easy. Once I tried continuous aggregates, I realized that TimescaleDB provided the solution that I (and many other PostgreSQL users) were looking for. Table comparing the functionality of PostgreSQL materialized views with continuous aggregates in TimescaleDB
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