Serving data storage layer

The serving analytical data storage layer is responsible for persisting the transformed, enriched, and validated data produced by the data processing layer in data stores that maintain the data model structures so that they are ready to serve downstream data intelligence and data insight applications. This minimizes or removes the need for further data transformations since the data is already persisted in highly-optimized data structures relevant to the type of processing required. The types of data stores provisioned in the serving analytical data storage layer are dependent on business and analytical requirements, and may include any, or a combination of, the following (stated along with examples of open source implementations):

• Relational databases, such as PostgreSQL and MySQL
• Document databases, such as Apache CouchDB and MongoDB
• Columnar databases, such as Apache Cassandra and Apache HBase
• Key-value databases, such as Redis and Voldemort
• Graph databases and frameworks, such as Apache TinkerPop
• Search engines, such as Apache Lucene and Elasticsearch