+1. Maybe kylin can support materialized views someday.
> 在 2020年1月13日，14:58，Xiaoxiang Yu <[email protected]> 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" <[email protected]> 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 > <http://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 > <https://www.1keydata.com/datawarehousing/data-warehouse-definition.html> > > Best regards, > > Shaofeng Shi 史少锋 > Apache Kylin PMC > Email: [email protected] <mailto:[email protected]> > > Apache Kylin FAQ: https://kylin.apache.org/docs/gettingstarted/faq.html > <https://kylin.apache.org/docs/gettingstarted/faq.html> > Join Kylin user mail group: [email protected] > <mailto:[email protected]> > Join Kylin dev mail group: [email protected] > <mailto:[email protected]> > >
