Did you like it? Check out our blog to stay up to date: https://getindata.com/blog In this talk I would like to introduce you to Druid (http://druid.io/), a powerful open-source technology used by companies like Metamarkets, Yahoo, Netflix or eBay, that can be used to create Real-Time Interactive Analytics stack. Druid is a distributed columnar datastore, built specifically for exploratory analytics for OLAP workflows. With it you can build analytics on events streams that power your dashboards, your monitoring, business intelligence and exploratory tools. It can scale with your data, going to hundreds of nodes storing and analyzing petabytes or years of data, while keeping most of queries returning in subsecond time. All that on data that is explorable in few seconds after being ingested. I’m going to talk about Druid specifically, but also about other technologies involved in building Real-Time Analytics stack.

7. Master
dataset
Hadoop
files
Hive tables
Batch view
Query layer
Postgres?
>15 minutes
latency
Pre-computed
Pre-aggregated views
ETL
SLOW queries
Kafka

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{
"queryType" : "timeseries",
"dataSource" : "wikipedia",
"intervals" : "2013-01-01/2013-01-08" ,
"filter" : {
"type" : "selector",
"dimension" : "page",
"value" : "Ke$ha"
},
"granularity" : "day",
"aggregations" : [{"type":"count", "name":"rows"}]
}

17. events

18. events

20. 12:00 13:00 14:00

22. * Not mine

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24. Kafka

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28. Do you have any questions?