Apache Kylin Use Cases in China and Japan

Learn how enterprises across Asia are using Apache Kylin to enhance their business intelligence (BI) tools and analytics work.

Apache Kylin Best Practices

Discover what Apache Kylin makes possible with these analytics use cases from leading companies.

OLAP, the optimal choice for today’s analytics environment

Working with data today means working with massive datasets. After all, the more information you have, the better your decisions will be. Unfortunately, many BI solutions can’t handle large data volumes, and that leaves many analysts uncovering answers too late – if at all.

OLAP solves this problem. It ensures high-performance analytics on Big Data and allows companies to utilize all of their data to develop new ideas quickly. This guide explains how OLAP works and what you should know about the world’s leading OLAP solutions: Apache Kylin and Kyligence.

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See which OLAP approach is right for your organization

Across the globe, 1,000s of major enterprises have turned to Apache Kylin and Kyligence for their unique Augmented OLAP technology that has made it easier than ever for these companies and their IT departments to deliver peerless analytics performance and near-limitless concurrency to their analysts, all while bringing down operational overhead.

This comparison guide will walk you through the capabilities and limitations of these two solutions and explain the improvements they’ve brought to traditional OLAP that has made them the top choice for businesses looking to accelerate their analytics work on Big Data. With this guide, you’ll get:

 

  • A side-by-side comparison of Apache Kylin and Kyligence features.
  • A high-level explanation of both solutions and where they work best.
  • An overview of key capabilities for both Kylin and Kyligence.

 

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