Scaling Postgres for Time Series Data with the Citus Database | A Citus Conversation | Claire Giordano & Marco Slot

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November 14, 2018

Scaling Postgres for Time Series Data with the Citus Database | A Citus Conversation | Claire Giordano & Marco Slot

Claire Giordano interviewed Marco Slot, Principal Engineer at Citus Data, and they explored how you can use Postgres and Citus to scale your time series data.

If you're working with time series data, you are likely dealing with large volumes—and you might not be able to control the amount of data people are sending you. Especially if you need to do fairly advanced analytics, join us to learn:

-- How you can use PostgreSQL extensions such as pg_partman and Citus to scale out Postgres for time series data
-- How pg_partman does auto partitioning

Citus is an extension to Postgres that transforms Postgres into a distributed database—popular among SaaS developers building multi-tenant apps and teams building real-time analytics dashboards that require sub-second latency. What you might not know is that Citus is a good fit for time series data, especially in combination with new Postgres extensions such as pg_partman.

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Citus Data

November 14, 2018
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