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In computer science, Algorithms for Recovery and Isolation Exploiting Semantics, or ARIES, is a recovery algorithm designed to work with a no-force, steal database approach; it is used by IBM Db2, Microsoft SQL Server and many other database systems. [1] IBM Fellow Chandrasekaran Mohan is the primary inventor of the ARIES family of algorithms. [2]
One technique for evaluating database security involves performing vulnerability assessments or penetration tests against the database. Testers attempt to find security vulnerabilities that could be used to defeat or bypass security controls, break into the database, compromise the system etc. Database administrators or information security administrators may for example use automated ...
The main disadvantage associated with column-level database encryption is speed, or a loss thereof. Encrypting separate columns with different unique keys in the same database can cause database performance to decrease, and additionally also decreases the speed at which the contents of the database can be indexed or searched. [12]
Open-source, cross-platform C library to generate PDF files. OpenPDF: GNU LGPLv3 / MPLv2.0: Open source library to create and manipulate PDF files in Java. Fork of an older version of iText, but with the original LGPL / MPL license. PDFsharp: MIT C# developer library to create, extract, edit PDF files. Poppler: GNU GPL
Time series database: Greenplum Database C Support and extensions available from VMware. MapD: C++ MariaDB ColumnStore C & C++ Formerly Calpont InfiniDB: Metakit: C++ MonetDB: C Open-source (since 2004) columnar Relational DBMS pioneer PostgreSQL cstore fdw, [1] vops [2] C cstore_fdw uses ORC format StarRocks Java & C++
Isolation is typically enforced at the database level. However, various client-side systems can also be used. It can be controlled in application frameworks or runtime containers such as J2EE Entity Beans [2] On older systems, it may be implemented systemically (by the application developers), for example through the use of temporary tables.
Database activity monitoring (DAM, a.k.a. Enterprise database auditing and Real-time protection [1]) is a database security technology for monitoring and analyzing database activity. DAM may combine data from network-based monitoring and native audit information to provide a comprehensive picture of database activity.
Database auditing involves observing a database to be aware of the actions of database users. Database administrators and consultants often set up auditing for security purposes, for example, to ensure that those without the permission to access information do not access it.