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Tuesday, June 25 • 11:15am - 12:00pm
Creating Continuously Up to Date Materialized Aggregates

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Time-series workloads (i.e. data from sensors, IoT devices, finance, or even satellites) are generally insert-mostly, and data typically arrives in time order (at regular or irregular intervals). Given the high velocity and continuous workload of writing time-series, insert performance is paramount. But what is the use of inserting a significant amount of data if you can't analyze, visualize, and act on it effectively? Unlike many OLTP workloads, you often don't need the granularity of each data point, but rather reports on aggregates over significant periods of time and other analysis are the key to making good decisions with the data you store.

This talk describes how TimescaleDB (a time-series database packaged as an extension of PostgreSQL) has implemented the infrastructure for creating continuously up-to-date aggregates without write amplification using features of Postgres (partial aggregates, invalidation triggers, proper locking/transaction safety, background workers, union views, query planner etc.), as well as how/when to use these pre-calculated results to speed your queries.

avatar for David Kohn

David Kohn

Software Engineer, Timescale
After earning a B.S. in Environmental Engineering at Yale, founding an electrochemistry startup, joining a battery startup, and doing crazy things with Postgres for Moat (an ad-analytics company), David joined Timescale to focus on research and development. He also cooks, does pottery... Read More →

Tuesday June 25, 2019 11:15am - 12:00pm EDT
Back Bay B The Sheraton Boston Hotel, 39 Dalton St, Boston, MA, 02199