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Showing 3 open source projects for "https"
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MongoDB Atlas runs apps anywhereMongoDB 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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Cut Data Warehouse Costs up to 54% with BigQueryBigQuery delivers up to 54% lower TCO than cloud alternatives. Migrate from legacy or competing warehouses using free BigQuery Migration Service with automated SQL translation. Get serverless scale with no infrastructure to manage, compressed storage, and flexible pricing—pay per query or commit for deeper discounts. New customers get $300 in free credit.
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...A valid license key is required to activate and use the application. Enterprise security & AES-256 encryption for Windows systems Commercial and Enterprise licenses are available on our official website: https://www.coreguardtech.org Wichtiger Hinweis: Die TITAN Security Suite ist eine kommerzielle Software. Zur Aktivierung und Nutzung ist ein gültiger Lizenzschlüssel erforderlich. Kommerzielle und Enterprise-Lizenzen sind auf unserer offiziellen Website erhältlich: https://www.coreguardtech.org
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Open Source Data Quality and Profiling
World's first open source data quality & data preparation project
...It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. This project is also known as "Aggregate Profiler" Resful API for this project is getting built as (Beta Version) https://sourceforge.net/projects/restful-api-for-osdq/ apache spark based data quality is getting built at https://sourceforge.net/projects/apache-spark-osdq/ -
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also.
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