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The JDBC classes are contained in the Java package java.sql and javax.sql. Starting with version 3.1, JDBC has been developed under the Java Community Process. JSR 54 specifies JDBC 3.0 (included in J2SE 1.4), JSR 114 specifies the JDBC Rowset additions, and JSR 221 is the specification of JDBC 4.0 (included in Java SE 6). [2]
It simplifies coding compared to JDBC. SQL statements are executed with a single line. MyBatis provides a mapping engine that maps SQL results to object trees in a declarative way. SQL statements can be built dynamically by using a built-in language with XML-like syntax or with Apache Velocity using the Velocity integration plugin.
A JDBC driver is a software component enabling a Java application to interact with a database. [1] JDBC drivers are analogous to ODBC drivers , ADO.NET data providers , and OLE DB providers . To connect with individual databases, JDBC (the Java Database Connectivity API ) requires drivers for each database.
Maven will automatically download the dependency and the dependencies that Hibernate itself needs (called transitive dependencies) and store them in the user's local repository. Maven 2 Central Repository [2] is used by default to search for libraries, but one can configure the repositories to be used (e.g., company-private repositories) within ...
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.
Apache Drill is an open-source software framework that supports data-intensive distributed applications for interactive analysis of large-scale datasets. Built chiefly by contributions from developers from MapR, [1] [2] Drill is inspired by Google's Dremel system. [3]
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...