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Train ML Models With SQL You Already KnowBuild 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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1
Framework Benchmarks
Source for the TechEmpower Framework Benchmarks project
...With much help from the community, coverage is quite broad and we are happy to broaden it further with contributions. The project presently includes frameworks on many languages including Go, Python, Java, Ruby, PHP, C#, F#,Clojure, Groovy, Dart, JavaScript, Erlang, Haskell, Scala, Perl, Lua, C, and others. The current tests exercise plaintext responses, JSON serialization, database reads and writes via the object-relational mapper (ORM), collections, sorting, server-side templates, and XSS counter-measures. Future tests will exercise other components and greater computation. -
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fast-serialization
FST: fast java serialization drop in-replacement
Up to 10 times faster 100% JDK Serialization compatible drop-in replacement (Ok, might be 99% ..). As an example: Lambda Serialization which came with 1.8 worked instantly. Android compatible since version 2.17 (use FSTConfiguration.createAndroidDefaultConfiguration() both on the server and client side. The configuration object has to be passed into FSTObjectIn/Output constructors) FSTStructs is very similar to IBM's packed objects. The difference is you can run it with Oracle JDK today....
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