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  2. Lambda architecture - Wikipedia

    en.wikipedia.org/wiki/Lambda_architecture

    The two view outputs may be joined before presentation. The rise of lambda architecture is correlated with the growth of big data, real-time analytics, and the drive to mitigate the latencies of map-reduce. [1] Lambda architecture depends on a data model with an append-only, immutable data source that serves as a system of record.

  3. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    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).

  4. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [26] Big data requires a set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. [27]

  5. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Open source, scalable, distributed across a multi-machine cluster graph database under The Linux Foundation; supports various storage backends (Apache Cassandra, Apache HBase, Google Cloud Bigtable, Oracle Berkeley DB); [29] supports global graph data analytics, reporting, and extract, transform, load (ETL) through integration with big data ...

  6. Data architect - Wikipedia

    en.wikipedia.org/wiki/Data_architect

    A data architect is a practitioner of data architecture, a data management discipline concerned with designing, creating, deploying and managing an organization's data architecture. Data architects define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or ...

  7. Google Cloud Dataflow - Wikipedia

    en.wikipedia.org/wiki/Google_Cloud_Dataflow

    Google Cloud Dataflow was announced in June, 2014 [3] and released to the general public as an open beta in April, 2015. [4] In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs (data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. [5]

  8. Amazon Kinesis - Wikipedia

    en.wikipedia.org/wiki/Amazon_Kinesis

    Amazon Kinesis is a family of services provided by Amazon Web Services (AWS) for processing and analyzing real-time streaming data at a large scale. Launched in November 2013, it offers developers the ability to build applications that can consume and process data from multiple sources simultaneously. [2]

  9. Apache Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.