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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.
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The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
GGI stands for "General Graphics Interface", and it is a project that aims to develop a reliable, stable and fast graphics system that works everywhere. We want to allow any program using GGI to run on any platform requiring at most a recompile.
Converts (packages) Python programs into stand-alone executables
PyInstaller is a program that converts (packages) Python programs into stand-alone executables, under Windows, Linux, Mac OS X, AIX and Solaris. Its main advantages over similar tools are that PyInstaller works with any version of Python since 2.3, it builds smaller executables thanks to transparent compression, it is fully multi-platform, and uses the OS support to load the dynamic libraries, thus ensuring full compatibility.
Send/Receive/Reply messaging, popularized in commericial RTOS's such as QNX, is intuitive and simple to understand and an immensely powerful way of designing distributed software applications. This project aims to bring these tools to Linux.
cx_Oracle is a Python extension module that allows access to Oracle databases and conforms to the Python database API specification version 2.0
Project has moved to GitHub (https://github.com/oracle/python-cx_Oracle) and new builds are available at PyPI (https://pypi.python.org/pypi/cx_Oracle).
Cloud data warehouse to power your data-driven innovation
BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.