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.
With more than 20 years working in the IT industry, Olaf has earned experiences as architect, developer, administrator, trainer and project manager in many different areas. Storing and processing huge amounts of data, was always a focal point of his work. At ORDIX AG, he is responsible for Big Data and Data Warehouse technologies. He has built up a team of Big Data consultants, created several training courses, speaks at conferences and regularly publishes technical articles.
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