Postgres materialized views, for time-series data.
TimescaleDB will continuously compute your frequently used queries - in the background - so your data is available on-demand, without a performance hit.
Data is always changing
Collecting relentless streams of time-series data could result in slow queries as the system scans large amounts of information each query execution. You need to constantly recompute those queries in the background, so your information is available instantly when you need it.
You need TimescaleDB.
Better performance. Lower cost. Simpler operations. đź’Ş
Continuous aggregates work in the background, automatically processing SQL queries into materialized views as new data is added or old data is modified, according to a schedule.
Speed up your most common queries, so that your dashboards and visualizations render faster.
See continuous aggregates in action
Faster queries with time-series data on PostgreSQL: Continuous Aggregates in TimescaleDB
Developers ️❤️ TimescaleDB
“Continuous aggregates are what well and truly sold me on TimescaleDB. We went from 6.4 seconds to execute a query to 30ms. Yes, milliseconds.”
Caroline Rodewig, Senior Software Engineer and Predict Crew Lead at FlightAware
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“On average, I’m ingesting around 20k records/market, or 3.6 million total records, per day (20k*182 markets). This is where TimescaleDB started to shine for me. It gave me fast real-time aggregations, built-in time-series functions, and high ingestion rates.”
Felipe Queis, senior engineer and TimescaleDB community member
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