Filter By "real-time-analytics"
Imply Pivot delivers the final mile for modern analytics applications
This blog is focused on how Imply Pivot delivers the final mile for building an anlaytics app. It showcases two customer examples - Twitch and ironsource.
Building high performance logging analytics with Polaris and Logstash
When you think of querying with Apache Druid, you probably imagine queries over massive data sets that run in less than a second. This blog is about some of the things we did as a team to discover the user stories, define an asynchronous download API, and deliver it in a monthly STS release.
Announcing Imply Polaris
Today, we're excited to announce a major leap forward in ease-of-use with the introduction of Imply Polaris, our fully-managed, database-as-a-service.
Building Analytics for External Users is a Whole Different Animal
Analytics aren’t just for internal stakeholders anymore. If you’re building an analytics application for customers, then you’re probably wondering…what’s the right database backend?
The Rise of a New Analytics Hero in 2022
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
A new shape for Apache Druid
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.
Hot analytics and the data warehouse deficit
One of the most important considerations when selecting an analytics platform is its suitability to conduct the required analyses over specific types of data within a given performance threshold. A helpful way to think about this is to utilize the concept of temperature-tiered analytics to align analytics needs with data architectures.
A Reference Architecture for Real-Time IoT Analytics feat. Apache Druid
Analyzing the potential petabytes or more of data from all these devices goes way beyond existing data warehouses or data lakes. Fortunately companies have already implemented IoT analytics using Imply, the real-time intelligence platform built on Apache Druid, the leading open source real-time time analytics database.
Why Vertica Customers Adopt Apache Druid for Real-Time Analytics
If you are a Vertica customer, you probably already know this. Vertica is not built for real-time operational analytics at scale. If you do not know Vertica very well, you might be surprised. This statement may seem controversial. It’s not. Nearly ¼ of Imply customers were existing Vertica customers who purchased Imply, a commercially supported version of Apache Druid, because they were trying to implement operational analytics and hit limitations with Vertica. Other Vertica customers also use open source Druid and self-support.