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  • Druid Data Cookbook: Upserts in Druid SQL

    Nov 25, 2023 • blog, druid, sql, imply, adtech, tutorial, update, crud

    Druid Cookbook

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  • Druid SQL: BETWEEN considered harmful

    Nov 3, 2023 • blog, apache, druid, sql

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  • Druid 28 Sneak Peek: Ingesting Multiple Kafka Topics into One Datasource

    Oct 29, 2023 • blog, apache, druid, imply, streaming, kafka, tutorial

    Pizza

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  • New in Imply Polaris: Data Retention Policy

    Sep 24, 2023 • blog, imply, polaris, druid, data_lifecycle

    Apache Druid has always had built-in data lifecycle management by way of retention rules. Specifying fixed time intervals or relative periods, you would tell Druid to retain only data segments that are not older than x days.

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  • New in Apache Druid 27: Querying Deep Storage

    Sep 7, 2023 • blog, druid, imply, query, storage

    In realtime analytics, a common scenario is that you want to retain a lot of (years of) historical data in order to run analytics over a longer period of time. But these analytical queries occur infrequently and their performance is usually not critical. The bulk of everyday queries, however, accesses only a limited set of relatively fresh data, typically 1 or 2 weeks worth.

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