Apache Groovy vs. Crystal vs. Oracle Big Data SQL Cloud Service vs. Python Comparison Chart

Apache Groovy is a powerful, optionally typed and dynamic language, with static-typing and static compilation capabilities, for the Java platform aimed at improving developer productivity thanks to a concise, familiar and easy to learn syntax. It integrates smoothly with any Java program, and immediately delivers to your application powerful features, including scripting capabilities, Domain-Specific Language authoring, runtime and compile-time meta-programming and functional programming. Concise, readable and expressive syntax, easy to learn for Java developers. Closures, builders, runtime & compile-time meta-programming, functional programming, type inference, and static compilation. Flexible & malleable syntax, advanced integration & customization mechanisms, to integrate readable business rules in your applications. Great for writing concise and maintainable tests, and for all your build and automation tasks.

Oracle Big Data SQL Cloud Service enables organizations to immediately analyze data across Apache Hadoop, NoSQL and Oracle Database leveraging their existing SQL skills, security policies and applications with extreme performance. From simplifying data science efforts to unlocking data lakes, Big Data SQL makes the benefits of Big Data available to the largest group of end users possible. Big Data SQL gives users a single location to catalog and secure data in Hadoop and NoSQL systems, Oracle Database. Seamless metadata integration and queries which join data from Oracle Database with data from Hadoop and NoSQL databases. Utilities and conversion routines support automatic mappings from metadata stored in HCatalog (or the Hive Metastore) to Oracle Tables. Enhanced access parameters give administrators the flexibility to control column mapping and data access behavior. Multiple cluster support enables one Oracle Database to query multiple Hadoop clusters and/or NoSQL systems.