Fast analytics on fast data: Kudu as a storage layer for banking applications
Olaf Hein explains how a large German bank relies on a Kudu-based data platform to speed up business processes. Olaf highlights key data access patterns and the system architecture and shares best practices and lessons learned using Kudu in development and operations.
| Talk Title | Fast analytics on fast data: Kudu as a storage layer for banking applications |
| Speakers | Olaf Hein (ORDIX AG) |
| Conference | Strata Data Conference |
| Conf Tag | Making Data Work |
| Location | London, United Kingdom |
| Date | May 22-24, 2018 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
With HDFS and HBase, there are two different storage options available in the Hadoop ecosystem. Both have their strengths and weaknesses. However, neither HDFS nor HBase can be used universally for all kinds of workloads. Usually this leads to complex hybrid architectures. Kudu fills this gap and simplifies the architecture of big data systems. A large German bank is using a new data platform based on Kudu and Cloudera’s Enterprise Hadoop Distribution to speed up its credit processes. Within this system, financial transactions of millions of customers are analyzed by Spark jobs. In addition to this analytical workload, several frontend applications use the Kudu Java API to perform random reads and writes in real-time. Topics include:
