Search Results for "parallel"
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Showing 5 open source projects for "parallel"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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ClickHouse
A fast open-source OLAP database management system
ClickHouse® is a fast, open-source column-oriented database management system that can generate analytical data reports through SQL queries in real time. According to several independent benchmarks, it far exceeds other comparable column-oriented database management systems, working even up to 1000 times faster. It is able to process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. Apart from its blazing speed, ClickHouse is highly... -
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starrydb-publice
starrydb is game server engine
starrydb is game server engine, As long as a few simple scripts can help you quickly build a game server. email:admin@starrydb.com -
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Postgres-XC is a write-scalable synchronous multi-master PostgreSQL cluster with the following features. 1) Both read and write scalability. 2) Configured with more than one server. 3) Complete global transaction and visibility management.
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Telecommunication Application Transaction Processing Benchmark generates a transactional load over parallel client connections, targeted at a database system under test. It is modeled after a mobile network application HLR (Home Location Register).
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Automated RMM Tools | RMM SoftwareOut-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
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Ray improves throughput when many concurrent queries access large scientific databases. Queries are synchronized to access sectors on disk simultaneously so that an arbitrary number of parallel queries can be executed without degradation in performance.
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