Hello, The new slogan has been updated to Kylin website: https://kylin.apache.org/
Other places will be updated in the next days. Thanks to everybody! Best regards, Shaofeng Shi 史少锋 Apache Kylin PMC Email: shaofeng...@apache.org Apache Kylin FAQ: https://kylin.apache.org/docs/gettingstarted/faq.html Join Kylin user mail group: user-subscr...@kylin.apache.org Join Kylin dev mail group: dev-subscr...@kylin.apache.org ShaoFeng Shi <shaofeng...@apache.org> 于2020年1月21日周二 下午5:04写道: > Thanks to the ones who gave comments. This thread is still open for wider > discussion. I plan to update the home page in Feb, after the Chinese New > Year holiday. > > Best regards, > > Shaofeng Shi 史少锋 > Apache Kylin PMC > Email: shaofeng...@apache.org > > Apache Kylin FAQ: https://kylin.apache.org/docs/gettingstarted/faq.html > Join Kylin user mail group: user-subscr...@kylin.apache.org > Join Kylin dev mail group: dev-subscr...@kylin.apache.org > > > > > Luke Han <luke...@gmail.com> 于2020年1月19日周日 下午2:02写道: > >> +1, >> >> Kylin is helping many companies to manage their Golden Data for Big Data, >> and the most of use cases are for Analytics purpose. >> From OLAP to Analtyics DW is the destination of Kylin. >> >> looking forward to the legend to evolve to the next stage. >> >> Cool! >> >> Best Regards! >> --------------------- >> >> Luke Han >> >> >> On Mon, Jan 13, 2020 at 3:12 PM codingfor...@126.com < >> codingfor...@126.com> wrote: >> >>> +1. >>> Maybe kylin can support materialized views someday. >>> >>> >>> 在 2020年1月13日,14:58,Xiaoxiang Yu <x...@apache.org> 写道: >>> >>> +1 >>> Great suggestion. And I wish in the future, Kylin could support more and >>> more data source and provided better performance when build segment . >>> >>> >>> >>> >>> -- >>> *Best wishes to you ! * >>> *From :**Xiaoxiang Yu* >>> >>> At 2020-01-12 20:32:12, "ShaoFeng Shi" <shaofeng...@apache.org> wrote: >>> >>> Hello, Kylin developers and users, HAPPY NEW YEAR 2020! >>> >>> In last month, we released Kylin 3.0, with the new Real-time streaming >>> feature and a Lambda architecture. This allows our users to host only one >>> system for both batch and real-time analytics, and then can query batch and >>> streaming data together. >>> >>> If you look at Kylin's home page, its slogan is still the "OLAP Engine >>> for Big data", which was made 5 years ago when it was born. While today, >>> Kylin's capability has been verified beyond an "OLAP engine". I visited >>> many Kylin users in China, US, Euro in last year, and have got many >>> different scenarios: >>> >>> 1. eBay initiated the Kylin project to offload analytical workloads from >>> Teradata to Hadoop; Kylin serves the online queries with high performance >>> and high availability. Till today, Kylin serves millions of queries every >>> day, most are in < 1 seconds; >>> 2. China Unionpay and CPIC use Kylin to replace IBM Cognos cubes. One >>> Kylin cube replaced more than 100 Cognos cubes, with better building >>> performance and query performance. >>> 3. China Construction Bank uses Hadoop + Kylin to offload the Greenplum. >>> Some systems have been migrated to Kylin successfully. >>> 4. Yum (KFC) and several other users are using Kylin to replace >>> Microsoft SSAS. >>> 5. Meituan, Ctrip, JD, Didi, Xiao Mi, Huawei, OLX group, autohome.com.cn, >>> Xactly, and many others are using Kylin as the platform of their DaaS (Data >>> as a Service), providing data service to their thousands of internal >>> analysts and tens of thousands of external tenants. >>> >>> Now let's look at the definition of Data warehouse [1]: >>> >>> "*A data warehouse is a subject-oriented, integrated, time-variant and >>> non-volatile collection of data in support of management's decision-making >>> process.*" >>> >>> In Kylin, each model/cube is created for a certain subject; Kylin >>> integrates well with Hive, Hadoop, Spark, Kafka, and other systems; Kylin >>> incremental loads the data by time, build the cube and then save as >>> segments (partitions), and they are non-volatile unless you refresh them; >>> During the analysis (roll-up, drill-down, etc), the data is always >>> consistent. Kylin provides SQL interface and JDBC/ODBC/HTTP API for you to >>> easily connect from BI/visualization tools like Tableau and others. >>> >>> All in all, you can see that users are using Kylin not just as a SQL >>> engine, but also as an Analytical Data Warehouse, for very large scale data >>> (PB scale). In the world of big data, Kylin is unique. Its design is >>> elegant, its architecture is scalable and pluggable. In order to give >>> Kylin more visibility and can be discovered by more people, I propose to >>> change Kylin's position/slogan from the "OLAP engine for big data" to >>> "Analytical Data warehouse for big data". >>> >>> Please feel free to share your comments. >>> >>> [1] >>> https://www.1keydata.com/datawarehousing/data-warehouse-definition.html >>> >>> Best regards, >>> >>> Shaofeng Shi 史少锋 >>> Apache Kylin PMC >>> Email: shaofeng...@apache.org >>> >>> Apache Kylin FAQ: https://kylin.apache.org/docs/gettingstarted/faq.html >>> Join Kylin user mail group: user-subscr...@kylin.apache.org >>> Join Kylin dev mail group: dev-subscr...@kylin.apache.org >>> >>> >>> >>>