Couchbase Query Language, known as N1QL and pronounced "Nickel", is a query language for finding data in Couchbase Server. N1QL is designed to be human readable and writable. It is a language designed for ad-hoc querying. The query language is a standard semantic used to build querying ability in other databases.
he LUPOSDATE SPARQL system supports various approaches to manage RDF data and process SPARQL queries: Index, RDF3X, Stream, Jena and Sesame. Jena  and Sesame  refer to third-party SPARQL engines. Index is our in-memory Engine presented in . Stream is our stream-based implementation (see ). RDF3X is a re-implementation of , but is further enhanced with additional optimization strategies.
What is Lily?
HTSQL was created in 2005 to provide an XPath-like HTTP interface to PostgreSQL for client-side XSLT screens and reports. HTSQL found its audience when analysts and researchers bypassed the user interface and started to use URLs directly. The language has evolved since then.
Carrot is not the first XSLT-inspired project to provide a shorter syntax than XSLT itself. Syntax shorthands have included Paul Tchistopolskii's XSLScript, Sam Wilmott's RXSLT, and another project called XSLTXT. Although none of these projects provided direct inspiration for Carrot, they all address one of the same desires that Carrot addresses: being able to program in XSLT more concisely
EGL is not just another language (really). Our philosophy is that developing for a new platform should not force learning a new language.
Common language, syntax, and programming model across all parts of the application, regardless of where the code is deployed.
Leverages proven, existing platforms (like web browsers and Java VMs) and technologies (like Dojo, ExtJS, Java JPA) by compiling into efficient, lower-level code.
Complements (does not replace) existing technologies and existing infrastructure investments.
Proven technology that is used by hundreds of enterprise customers all over the world.
Extensible compiler and code generation framework that supports adaptation to the unique needs of specific developer communities and changing requirements.
Think of EGL as "modeling in code". See our original project proposal for additional background information.