With any open source technology that’s been around for a while, misconceptions and myths about what tech can or can’t do inevitably pop up. Sometimes there’s some truth but often, it’s either an outdated perception or sometimes, it’s just that you need to do things differently. Apache Druid is no exception.
Since Druid was designed for fast queries on large-scale datasets and primarily focuses on aggregating and filtering data across dimensions and measures, you’ve probably heard someone lament that it can’t do joins. Or maybe you’ve heard someone say that Druid isn’t great with updates. Or maybe you’ve even thought to yourself “Druid would be so much better if it was easier to set up.”
In this session, we’ll debunk those pesky Druid myths and talk about how Druid handles joins, updates, and more. We’ll also dive into where those ideas came from, what Druid is built for specifically, and invite you to look at Druid as not just another database.
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