Founded by the creators of Apache Kylin, venture-backed Kyligence and is dual-headquartered in San Jose, California, and Shanghai, China. Earlier this year, the company added a new funding round to continue its focus on accelerating customer productivity by automating data management, discovery, interaction, and insight generation. Luke Han, co-founder and CEO at Kyligence, recently explained the company’s connection to the open source project, its future goals, where it fits into the global data management ecosystem, and how it plans to differentiate itself from competitors.
Kyligence announced a $70 million Series D funding round in April. What is the plan for this putting the new investment to work?
Luke Han: The funds provided by our investors will focus on three major areas. First, we have ambitious plans to continue to innovate and enhance our products with greater levels of automation through the expanded use of machine learning and AI, and a full cloud native architecture for better flexibility and scale. This new level of intelligent automation will include continued focus on creating an exceptional user experience to simplify data management and analytics by expanding our automated expert recommendations.
What are your additional goals?
LH: Second, we will continue to invest in the open-source community with new contributions to the Apache Kylin project. We will further introduce new open-source projects that will focus on simplifying the adoption and use of machine learning and AI. Third, we will accelerate our global expansion with a world class go-to-market initiative and an expanded sales and business development footprint. We will also enhance our global partner ecosystem with industry leading cloud vendors, system integrators, and independent software vendors.
"The data analytics market has changed from decision support systems to democratized analytics—an 'analytics civilization,' if you like."
For people who are not familiar with the Apache Kylin project, what does it offer?
LH: Kylin is an open source project under Apache Software Foundation contributed by eBay in 2014. It is a distributed OLAP platform that is responsible for delivering predictable, sub-second response times for SQL queries of datasets at petabyte scale. The project has been adopted by more than 1500 organizations worldwide including eBay, Meituan, Baidu, Cisco, Microsoft, Tencent, OLX, and many others.
How is Kyligence related to Kylin?
LH: Kyligence was formed by creators of Apache Kylin in 2016. It provides an enterprise grade data analytics platform based on Apache Kylin that runs both on-premises and in the cloud. Kyligence has extended the capabilities of Kylin by introducing advanced features like an AI-augmented engine, a cloud native architecture, and a host of enterprise grade features. Through automation and AI, Kyligence makes operating data analytics faster, easier, and much more cost-effective. The company name is derived from the combination of Kylin and intelligence: Kyligence.
What does Kyligence offer customers that is not available through Kylin alone?
LH: Kyligence offers an enhanced unified semantic layer that amplifies the productivity of BI and data science teams by providing a centralized, well-governed golden dataset across different data sources. The platform also provides a unified SQL and MDX [MultiDimensional eXpressions] interface for all downstream consumers including BI tools, machine learning frameworks, and APIs from other systems.
Kyligence adds an automation layer to make recommendations for creating and evolving data models from SQL histories, suggesting optimizations for slow queries, and executing smart pushdown for ad-hoc queries.
Finally, with a strong and growing global partner network, Kyligence works with all leading cloud platforms—Azure, AWS, and others—and BI tools, such as PowerBI, Tableau, MicroStrategy. With Kyligence, data analysts can even access and analyze petabyte-scale datasets through their secret weapon, Microsoft Excel, without having to export or import data to and from Excel.
How does the technology differ from what is offered through other open source projects?
LH: Apache Kylin focuses on generic OLAP rather than other purpose-built OLAP systems, such as time series databases. In that world, Kylin is more suited for human beings doing analytics work. The biggest difference is the crucial balance between space and time: more storage space for less query time—latency. For most applications, a small investment in data storage can save a fortune in processing time. Another advantage of Kylin/Kyligence is vastly increased concurrency which enables many use cases that boil down to delivering data-as-a-service for AI, machine learning, and SaaS infrastructure.
Are there other software products that are compatible, or required to work with Kyligence?
LH: Kyligence is already certified with leading Hadoop platforms, cloud platforms, and BI tools like Tableau, PowerBI, MicroStrategy, and even open source tools like Apache Superset.
Does Kyligence help to overcome some of the limitations with Hadoop?
LH: Most Hadoop workloads are about data marts and data warehousing. Kyligence provides cutting-edge technology to offload such workloads from Hadoop with greater efficiency, concurrency, and performance. Today, with Kyligence those workloads can be readily migrated to public cloud platforms or private on-prem clouds, without any Hadoop dependencies.