Open sourced in October of 2014, and graduated to an Apache Top-Level Project in November 2015, Apache Kylin has become the leading open source OLAP (Online Analytic Processing) engine for Big Data. Apache Kylin provides sub-second query latency on trillions of records and integrates existing Hadoop and BI systems seamlessly. It is a powerful framework in the Big Data landscape and has been adopted by thousands of organizations worldwide.
Recognized throughout the Big Data analytics and OLAP technology industry for its global impact on streamlining analytics operations, Apache Kylin has been awarded InfoWorld’s Bossie Awards for Best Open Source Big Data Tool 2015 & 2016.
To better serve the sophisticated needs of global enterprises, the team behind Apache Kylin launched Kyligence. Leveraging the transformative power of extreme OLAP on Big Data, Kyligence provides a suite of capabilities and improvements not found in Apache Kylin to offer a commercial, enterprise-level analytics solution for on-premises, hybrid, and cloud environments.
As the first open source distributed extreme OLAP engine that builds cubes on Hadoop, and powered by Hadoop/HBase/Spark and other technologies, Apache Kylin achieves millisecond to second level query latency for up to a trillion rows data. This means analysts and researchers can quickly extract insights from massive datasets interactively.
All operations can be done via web GUI, and the query language is ANSI-SQL so users don’t need to learn a new language. Apache Kylin also supports star and snowflake schemas, and you can easily migrate legacy applications to Hadoop. With the JDBC/ODBC driver, you can seamlessly integrate Apache Kylin with all of your BI tools.
Apache Kylin talks with Hadoop via standard APIs and can be quickly installed into all mainstream Hadoop releases, both on-premises and in the cloud. Apache Kylin exposes its Restful API so you can easily embed it into any data workflows you have.
Forget what you know about last-generation OLAP technology, the OLAP engine Apache Kylin provides is built for today’s Big Data challenges.
The OLAP cube and analytics capabilities Apache Kylin enables does away with rigid manual modeling, heavy maintenance dependencies, OLAP cube size limits, and difficult to scale architectures. Instead, you get an OLAP solution that surpasses the speed and performance of In-memory, massively parallel processing, data virtualization, and heterogeneous systems, even at petabyte scale.
When it comes to generating the fastest possible insights from Big Data, augmented OLAP analytics can’t be beat. But what solution is right for you: Apache Kylin or Kyligence?
In order to make the right choice you need to know the facts. Fortunately, we’ve pulled together our OLAP experts to create an easy to follow overview of each solution’s features and capabilities.
Written by members of the original team behind Apache Kylin, this guide delivers the side-by-side comparison you’re looking for to know which OLAP engine and Big Data platform will give you the performance you need.
Download this OLAP analytics comparison guide for Apache Kylin and Kyligence today. Don’t waste another minute on slow business intelligence.