Apache Impala vs. Oracle Big Data SQL Cloud Service vs. Python vs. Racket Comparison Chart

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.

Racket is a general-purpose, multi-paradigm programming language that serves as a modern dialect of Lisp and a descendant of Scheme. It is designed as a platform for programming language design and implementation, enabling developers to create new domain-specific and general-purpose languages. Racket's core language includes features such as macros, modules, lexical closures, tail calls, delimited continuations, parameters (fluid variables), software contracts, green threads, and OS threads. The language also comes with primitives, such as event spaces and custodians, which control resource management and enable the language to act like an operating system for loading and managing other programs. Further extensions to the language are created with the powerful macro system, which, together with the module system and custom parsers, can control all aspects of a language. Most language constructs in Racket are implemented as macros in the base language.