BigQuery automates data prep, analysis, and predictions with built-in AI assistance.
Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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MongoDB Atlas runs apps anywhere
Deploy in 115+ regions with the modern database for every enterprise.
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
RANGE: produce random genetic transcription networks in the NEMO language, which when compiled outputs models in Systems Biology Markup Language. Generate synthetic microarray data, or use NEMO alone to SBML-ize a network, or visualize it in cytoscape.
JSEXT is a framework for JavaScript for server scripts, web servers and web clients. Seamlessly integrates C libraries with JavaScript code. Based on this, JSEXT provides support for fastcgi, MySQL, SQLite, FTP, SMTP, HTTP and more.
Given YACC-like and LEX-like input files, yagg generates a C++ program that generates all strings of a user-specified length. yagg is easy to use, and provides a means of generating test inputs or validating a parser grammar by inspecting the strings.
Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
The CCC Language is yet another programming language. It is platform-independent, compact, and robust. Supports many SQL engines, has own ISAM DB engine, has terminal mode and more UI-s, is object-oriented, but it is compiled and not interpreted.
A parsing toolkit that supports both top-down (LL(1) and Simple Precedence) and bottom-up parsing (LR(0), SLR(1), LR(1) and LALR(1)). The toolkit supports generating Java parsers for all the bottom-up parsing methods, based on a CUP definition.