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A transactional table is the most basic and fundamental. The grain associated with a transactional fact table is usually specified as "one row per line in a transaction", e.g., every line on a receipt. Typically a transactional fact table holds data of the most detailed level, causing it to have a great number of dimensions associated with it.
A data lake can include structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). [3] A data lake can be established on premises (within an organization's data centers) or in the cloud (using cloud services).
Aster Data Systems: Proprietary CA Datacom: Proprietary CA IDMS: Proprietary Clarion: Proprietary ClickHouse: Apache License 2.0 Clustrix: Proprietary CockroachDB: Proprietary CSQL: Proprietary CUBRID: Apache, BSD DataEase: Proprietary DataFlex: Proprietary Dataphor: Proprietary dBase: Proprietary Derby (aka Java DB) Apache License 2.0 Empress ...
The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [ 2 ] The star schema gets its name from the physical model's [ 3 ] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.
The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]
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In October 2014, Snowflake came out of stealth mode; at that time it was used by 80 organizations. [3] [4] Snowflake has run on Amazon Web Services since 2014, [5] [6] on Microsoft Azure since 2018, [7] and on the Google Cloud Platform since 2019. [8] [9] In June 2015, Snowflake launched its first product, its cloud data warehouse. [10]
The RANK() OVER window function acts like ROW_NUMBER, but may return more or less than n rows in case of tie conditions, e.g. to return the top-10 youngest persons: SELECT * FROM ( SELECT RANK () OVER ( ORDER BY age ASC ) AS ranking , person_id , person_name , age FROM person ) AS foo WHERE ranking <= 10