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

Crystal’s syntax is heavily inspired by Ruby’s, so it feels natural to read and easy to write, and has the added benefit of a lower learning curve for experienced Ruby devs. Crystal is statically type-checked, so any type errors will be caught early by the compiler rather than fail on runtime. Moreover, and to keep the language clean, Crystal has built-in type inference, so most type annotations are unneeded. All types are non-nilable in Crystal, and available variables are represented as a union between the type and nil. As a consequence, the compiler will automatically check for null references in compile time. Crystal’s answer to metaprogramming is a powerful macro system, which ranges from basic templating and AST inspection to types inspection and running arbitrary external programs.

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.