jmng :
A \"Data warehouse\" is mostly an information systems concept that describes a centralized and trusted source of (e.g. company/business) data.\n\nFrom Wikipedia: \"DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise.\"\n\nRegarding your questions, a simple answer would be:\n\n\nGoogle BigQuery is a query execution (and/or data processing) engine that you can use over data stores of different kinds.\nGoogle BigTable is a database service that can be used to implement a\ndata warehouse or any other data store.\nGoogle DataProc is a data processing service composed by common Hadoop processing components like MapReduce (or Spark, if you consider it part of Hadoop).\nHadoop is a framework/platform for data storage and processing comprised of\ndifferent components (e.g. data storage via HDFS, data processing via MapReduce). You could use an Hadoop platform to build a Data Warehouse, e.g. by using MapReduce to process data and load it into ORC files that will be stored in HDFS and that can be queried by Hive. But it would only be appropriate to call it a data warehouse if it is a \"centralized, single version of the truth about data\" ;)\n",
2018-09-26T17:04:32