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When a Java application needs a database connection, one of the DriverManager.getConnection() methods is used to create a JDBC Connection. The URL used is dependent upon the particular database and JDBC driver. It will always begin with the "jdbc:" protocol, but the rest is up to the particular vendor.
The driver converts JDBC method calls into ODBC function calls. The driver is platform-dependent as it makes use of ODBC which in turn depends on native libraries of the underlying operating system the JVM is running upon. Also, use of this driver leads to other installation dependencies; for example, ODBC must be installed on the computer ...
A JDBC-ODBC bridge consists of a JDBC driver which employs an ODBC driver to connect to a target database. This driver translates JDBC method calls into ODBC function calls. Programmers usually use such a bridge when a given database lacks a JDBC driver, but is accessible through an ODBC driver.
In software engineering, a connection pool is a cache of reusable database connections managed by the client or middleware. It reduces the overhead of opening and closing connections, improving performance and scalability in database applications.
Reflection is used to instantiate classes and invoke methods using their names, a concept that allows for dynamic programming. Classes, interfaces, methods, fields, and constructors can all be discovered and used at runtime. Reflection is supported by metadata that the JVM has about the program.
Tool support for writing and debugging stored procedures is often not as good as for other programming languages, but this differs between vendors and languages. For example, both PL/SQL and T-SQL have dedicated IDEs and debuggers. PL/PgSQL can be debugged from various IDEs.
Collection of APIs used in cryptography. It includes APIs for both the Java and the C# programming languages. Burningwave Core: Java library to build frameworks. Cascading: Abstraction layer for Apache Hadoop and Apache Flink. Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language.
Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).