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Example of a database that can be used by a data lake (in this case structured data) A data lake is a system or repository of data stored in its natural/raw format, [1] usually object blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc., [2] and transformed data ...
Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
A data hub differs from a data lake by homogenizing data and possibly serving data in multiple desired formats, rather than simply storing it in one place, and by adding other value to the data such as de-duplication, quality, security, and a standardized set of query services. A data lake tends to store data in one place for availability, and ...
Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake". [40] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema. [41]
More generally, the term data platform can refer to any software platform used for collecting and managing data. It is an integrated solution which as of the 2010s can combine functionalities of for example a data lake, data warehouse or data hub for business intelligence purposes. [4]
Other data warehouses (or even other parts of the same data warehouse) may add new data in a historical form at regular intervals – for example, hourly. To understand this, consider a data warehouse that is required to maintain sales records of the last year. This data warehouse overwrites any data older than a year with newer data.
Data Lake Analytics is a parallel on-demand job service. The parallel processing system is based on Microsoft Dryad. [4] Dryad can represent arbitrary Directed Acyclic Graphs (DAGs) of computation. Data Lake Analytics provides a distributed infrastructure that can dynamically allocate resources so that customers pay for only the services they use.
Cloudera markets these products for purposes related to machine learning and data analysis. [1] Cloudera has adopted the marketing term "data lakehouse," which derives from a combination of the terms "data lake" and "data warehouse." [citation needed] Cloudera has formed partnerships with companies such as Dell, [27] IBM, [28] [29] and Oracle.