Filter By "big-data"

We obviously talk a lot about #ApacheDruid on here. But what are folks actually building with Druid? What is a modern analytics application, exactly? Let's find out

Elasticity is important, but beware the database that can only save you money when your application is not in use. The best solution will have excellent price-performance under all conditions.

Horizontal scaling is the key to performance at scale, which is why every database claims this. You should investigate, though, to see how much effort it takes, especially compared to Apache Druid.

After over 30 years of working with data analytics, we’ve been witness (and sometimes participant) to three major shifts in how we find insights from data - and now we’re looking at the fourth.

Every year industry pundits predict data and analytics becoming more valuable the following year. But this doesn’t take a crystal ball to predict. There’s instead something much more interesting happening that’s going to change everything in the analytics world

Today, I'm prepared to share our progress on this effort and some of our plans for the future. But before diving further into that, let's take a closer look at how Druid's core query engine executes queries, so we can then compare it with the multi-stage approach.

Everything is going to fail. If this is your first time working with or building out a distributed system, the fact that everything is going to fail may seem like an extremely scary concept, but it is one you will always have to keep in mind.

I recently read a great article by Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky that showcases the various techniques for visualizing and interacting with diverse data sets. I thought it may be useful to write something similar to showcase the various open source systems that exist in the “big data” space, including Druid, which is an open source data store I work on.