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2. Data lake - Wikipedia

   en.wikipedia.org/wiki/Data_lake

   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 ...

3. Databricks - Wikipedia

   en.wikipedia.org/wiki/Databricks

   Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake". [41] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema. [42]

4. Data warehouse - Wikipedia

   en.wikipedia.org/wiki/Data_warehouse

   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 ...

5. Change data capture - Wikipedia

   en.wikipedia.org/wiki/Change_data_capture

   In databases, change data capture (CDC) is a set of software design patterns used to determine and track the data that has changed (the "deltas") so that action can be taken using the changed data. The result is a delta-driven dataset .

6. Utah Data Center - Wikipedia

   en.wikipedia.org/wiki/Utah_Data_Center

   The Utah Data Center (UDC), also known as the Intelligence Community Comprehensive National Cybersecurity Initiative Data Center, [1] is a data storage facility for the United States Intelligence Community that is designed to store data estimated to be on the order of exabytes or larger. [2]

7. lakeFS - Wikipedia

   en.wikipedia.org/wiki/LakeFS

   lakeFS is a data versioning engine that manages data in a way similar to code. By using operations such as branching, committing, merging, and reverting, which resemble those found in Git, it facilitates the handling of data and its corresponding schema throughout the entire data life cycle.

8. Apache Iceberg - Wikipedia

   en.wikipedia.org/wiki/Apache_Iceberg

   Apache Iceberg is a high performance open-source format for large analytic tables.Iceberg enables the use of SQL tables for big data while making it possible for engines like Spark, Trino, Flink, Presto, Hive, Impala, StarRocks, Doris, and Pig to safely work with the same tables, at the same time. [1]

9. Data warehouse appliance - Wikipedia

   en.wikipedia.org/wiki/Data_warehouse_appliance

   "Data warehouse appliance" is a term coined by Foster Hinshaw, [1] [2] the founder of Netezza.In creating the first data warehouse appliance, Hinshaw and Netezza used the foundations developed by Model 204, Teradata, and others, to pioneer a new category to address consumer analytics efficiently by providing a modular, scalable, easy-to-manage database system that’s cost effective.