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Azure Data Lake service was released on November 16, 2016. It is based on COSMOS, [2] which is used to store and process data for applications such as Azure, AdCenter, Bing, MSN, Skype and Windows Live.
Data lakehouses are a hybrid approach that can ingest a variety of raw data formats like a data lake, yet provide ACID transactions and enforce data quality like a data warehouse. [ 14 ] [ 15 ] A data lakehouse architecture attempts to address several criticisms of data lakes by adding data warehouse capabilities such as transaction support ...
Azure Data Factory is a data integration service that allows creation of data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. [30] Azure Data Lake is a scalable data storage and analytic service for big data analytics workloads that require developers to run massively parallel queries.
Azure Data Explorer is a fully-managed [1] big data analytics cloud platform [2] [3] and data-exploration service, [4] developed by Microsoft, [5] [6] that ingests structured, semi-structured (like JSON) and unstructured data (like free-text).
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format. This enables faster loading times.
Data mesh is a sociotechnical approach to building a decentralized data architecture by leveraging a domain-oriented, self-serve design (in a software development perspective), and borrows Eric Evans’ theory of domain-driven design [1] and Manuel Pais’ and Matthew Skelton’s theory of team topologies. [2]
Cloud computing architecture; Cloud Computing Manifesto; Cloud computing research; Cloud computing security; Cloud database; Cloud engineering; Cloud Infrastructure Management Interface; Cloud load balancing; Cloud management; Cloud manufacturing; Cloud printing; Cloud robotics; Cloud Security Alliance; Cloud testing; Cloud-based integration ...
Azure SQL Database includes built-in intelligence that learns app patterns and adapts them to maximize performance, reliability, and data protection. Key capabilities include: Learning of the host app's data access patterns, adaptive performance tuning, and automatic improvements to reliability and data protection.