Druid is an open-source analytics data store designed for business intelligence (OLAP) queries on event data. Druid provides low latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is most commonly used to power user-facing analytic applications.
Druid and the Druid logo are copyright Metamarkets Group Inc.
Druid is a registered trademark of Metamarkets Group Inc.
|Sub-Second Queries||Druid delivers sub-second queries, even when you have terabytes of data and dozens of dimensions.|
|Real-Time Data Ingestion||Druid makes real-time a reality. Query data seconds after it arrives. Native integration with Apache Kafka makes it simple to enable real-time analytics.|
|Integrated with Apache Hive||Build OLAP cubes and run sub-second SQL queries using any Hive-compatible tool.|
|Apache Ambari Integration||Apache Ambari makes deploying, configuring and monitoring Druid a breeze..|
Hortonworks focuses on enabling fast, scalable analytics that seamlessly combines historical and real-time data.
Introduction Hadoop has always been associated with BigData, yet the perception is it’s only suitable for high latency, high throughput queries. With the contribution of the community, you can use Hadoop interactively for data exploration and visualization. In this tutorial you’ll learn how to analyze large datasets using Apache Hive LLAP on Amazon Web Services […]
A very common request from many customers is to be able to index text in image files; for example, text in scanned PNG files. In this tutorial we are going to walkthrough how to do this with SOLR. Prerequisites Download the Hortonworks Sandbox Complete the Learning the Ropes of the HDP Sandbox tutorial. Step-by-step guide […]
Introduction In this tutorial, you will learn about the different features available in the HDF sandbox. HDF stands for Hortonworks DataFlow. HDF was built to make processing data-in-motion an easier task while also directing the data from source to the destination. You will learn about quick links to access these tools that way when you […]
Introduction JReport is a embedded BI reporting tool can easily extract and visualize data from the Hortonworks Data Platform 2.3 using the Apache Hive JDBC driver. You can then create reports, dashboards, and data analysis, which can be embedded into your own applications. In this tutorial we are going to walkthrough the folllowing steps to […]
The Hortonworks Sandbox is delivered as a Dockerized container with the most common ports already opened and forwarded for you. If you would like to open even more ports, check out this tutorial.
Introduction R is a popular tool for statistics and data analysis. It has rich visualization capabilities and a large collection of libraries that have been developed and maintained by the R developer community. One drawback to R is that it’s designed to run on in-memory data, which makes it unsuitable for large datasets. Spark is […]
Apache Zeppelin on HDP 2.4.2 Author: Vinay Shukla In March 2016 we delivered the second technical preview of Apache Zeppelin, on HDP 2.4. Meanwhile we and the Zeppelin community have continued to add new features to Zeppelin. These features are now available in the final technical preview of Apache Zeppelin. This technical preview works with […]
Welcome to the Hortonworks Sandbox! Look at the attached sections for sandbox documentation.
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