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  2. Character large object - Wikipedia

    en.wikipedia.org/wiki/Character_large_object

    A Character Large OBject (or CLOB) is part of the SQL:1999 standard data types.It is a collection of character data in a database management system, usually stored in a separate location that is referenced in the table itself.

  3. Change data capture - Wikipedia

    en.wikipedia.org/wiki/Change_data_capture

    This technique can either supplement or complement timestamps and versioning. It can configure an alternative if, for example, a status column is set up on a table row indicating that the row has changed (e.g., a boolean column that, when set to true, indicates that the row has changed).

  4. Object storage - Wikipedia

    en.wikipedia.org/wiki/Object_storage

    Object storage (also known as object-based storage [1] or blob storage) is a computer data storage approach that manages data as "blobs" or "objects", as opposed to other storage architectures like file systems, which manage data as a file hierarchy, and block storage, which manages data as blocks within sectors and tracks. [2]

  5. Comparison of relational database management systems - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_relational...

    Note (3): "For other than InnoDB storage engines, MySQL Server parses and ignores the FOREIGN KEY and REFERENCES syntax in CREATE TABLE statements. The CHECK clause is parsed but ignored by all storage engines." [73] Note (4): Support for Unicode is new in version 10.0. Note (5): MySQL provides GUI interface through MySQL Workbench.

  6. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic. Connected-component labeling is not to be confused with segmentation.

  7. Data lake - Wikipedia

    en.wikipedia.org/wiki/Data_lake

    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).

  8. SQL syntax - Wikipedia

    en.wikipedia.org/wiki/SQL_syntax

    SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.

  9. Prepared statement - Wikipedia

    en.wikipedia.org/wiki/Prepared_statement

    Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.