Bring OLAP Back to Big Data!
Apache Kylin™ is an open source, distributed Analytical Data Warehouse for Big Data; it was designed to provide OLAP (Online Analytical Processing) capability in the big data era. By renovating the multi-dimensional cube and precalculation technology on Hadoop and Spark, Kylin is able to achieve near constant query speed regardless of the ever-growing data volume. Reducing query latency from minutes to sub-second, Kylin brings online analytics back to big data.
Apache Kylin™ lets you query billions of rows at sub-second latency in 3 steps.
Apache Kylin™ can also integrate with your favorite BI tools like Tableau and PowerBI etc., to enable BI on Hadoop.
Kylin is originally contributed from eBay Inc. in 2015.
Why Apache Kylin?
Timely Decision Making on Big Data
BI on Hadoop Accelerated
ANSI SQL Interface for Big Data on Hadoop
Interactive Queries at High Concurrency
Real-time OLAP for Streaming Big Data
MOLAP Cube Precalculation
- Job Management and Monitoring
- Compression and Encoding Support
- Incremental Refresh of Cubes
- Leverage HBase Coprocessor for query latency
- Both approximate and precise Query Capabilities for Distinct Count
- Approximate Top-N Query Capability
- Easy Web interface to manage, build, monitor and query cubes
- Security capability to set ACL at Project/Table Level
- Support LDAP and SAML Integration
Fundamental framework of Kylin OLAP Engine comprises of Metadata Engine, Query Engine, Job Engine and Storage Engine to run the entire stack. It also includes a REST Server to service client requests
Plugins to support additional functions and features
Lifecycle Management Support to integrate with Job Scheduler, ETL, Monitoring and Alerting Systems
Allows third party users to build customized user-interface atop Kylin core
ODBC and JDBC drivers to support different tools and products, such as Tableau