+1 Agreed. As Kylin has been equipped with plenty of "new" functionalities and is capable to suit various roles in analyzing data in large scale, a proper tag will definitely be much helpful not only to new users who are seeking for a suitable analyzing tool, but also to old users who want to explore possibilities in handling new scenarios with Kylin.
Bests, Xiaoyuan Gu 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
