Hadoop Application Architectures
Type: Analyst Research
Product: Data Integration, Big Data Analytics
Read this eBook for expert guidance on architecting end-to-end data management solutions with Apache Hadoop. This content will take you through architectural considerations necessary to build a complete tailored application based on your data integration use case.
- Data modeling in Hadoop including data storage options, HDFS schema design, HBase schema design, and managing metadata
- Data movement in Hadoop including data ingestion considerations (timeliness, incremental updates, access patterns, transformations, security, complexity, etc.) and options (file transfers, Sqoop, Flume, and Kafka)
"One of the most fundamental decisions to make when architecting a solution on Hadoop is determining how data will be stored in Hadoop. There is no such thing as a standard data storage format in Hadoop. Just as with a standard file system, Hadoop allows for storage of data in any format, whether it’s text, binary, images, etc."