Imply, founded by the original creators of Apache Druid®, develops an innovative database purpose-built for modern analytics applications. Imply is driving a new era in data analytics, called Analytics in Motion, where interactive queries, real-time and historical data at unlimited scale, combine with the best price/performance, to realize the full potential of data.
Hi Peter, it was a grand meetup yesterday... about Apache Druid, FlightRadar24 and more. Gratitude for the engaging talk. It was an awesome tech learning session!! 🙂👍
Here's a summary, as created by Google Bard: This video is about stream analytics and how it is different from traditional data warehousing and stream processing. The speaker, Darren, starts by defining what stream analytics is and why it is important. He then discusses the limitations of data warehouses and stream processors for real-time analytics. Finally, he introduces Apache Druid as a real-time database that can be used for stream analytics. Here are some key points from the video: Stream analytics is the process of analyzing data as it is being generated. Traditional data warehouses are not designed for real-time analytics because they require data to be loaded in batches. Stream processors can be used for real-time analytics, but they are limited in their ability to handle large amounts of data and complex queries. Apache Druid is a real-time database that can be used for stream analytics. It is designed to ingest data in real-time and to make it queryable immediately. Apache Druid can also be used to store historical data, which allows you to compare real-time data to historical data. If you are interested in learning more about stream analytics, I recommend watching this video. It is a great introduction to the topic and provides a lot of valuable information.
Thanks for making druid tutorial hands-on oriented with the 0.21 version. Now(feb2023) that i am in the 25.0.0 version how can i perform these hands-on .
I'm considering using druid and these lectures are highly valuable please post more deep dives. Also real life use cases with end to end design and implementation and how to unit test ingestion spec would be highly valuable.
