Linear Road - Home
A Stream Data Management Benchmark Stream Data Management System’s performance is measured by how many ‘Expressways’ a system can support by executing the required queries within a permitted time frame. The Linear Road Benchmark makes it possible to compare performance characteristics of Stream Data Management Systems relative to each other and relative to alternative systems like Relational Datab
SQL Parse, Analyze, Transform and Format All In One
Offline SQL syntax check Validates syntax without connecting to a database In-depth analysis of SQL script Prepares a detailed SQL parse tree node structure Custom SQL engine for various databases Includes query parser for DB2, Greenplum, Hana, Hive, Impala, Informix, MySQL, Netezza, Oracle, PostgreSQL Redshift SQL Server, Sybase, and Teradata, Highly customizable SQL formatter Highlights syntax w
ANTLR
What is ANTLR? ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build and walk parse trees. Terence Parr is a tech lead at Google and until 2022 was a professor of data science /
ITA Software by Google
Get your critical distribution projects off the ground ITA Software provides technology solutions for travel companies on the leading edge Unleash Your e-Commerce Creativity Deliver targeted, profitable e-Commerce experiences with QPX, a complete pricing, shopping and availability solution. Pricing & Shopping Revenue Shopping Engage customers with a rich shopping experience ReShop Shop for flight
GridGain — Extreme Speed and Scale for Data-Intensive Apps
GridGain is a Unified Real-Time Data Platform by the original creators of Apache Ignite. It enables a simplified and optimized data architecture for enterprises that require extreme speed, massive scale, and high availability from their data ecosystem. Flexible memory-first / disk-second architecture minimizes disk I/O to provide ultra-low latencies across transactional, streaming and analytical p
FFmpeg
Converting video and audio has never been so easy. $ ffmpeg -i input.mp4 output.avi News June 2rd, 2024, native xHE-AAC decoder FFmpeg now implements a native xHE-AAC decoder. Currently, streams without (e)SBR, USAC or MPEG-H Surround are supported, which means the majority of xHE-AAC streams in use should work. Support for USAC and (e)SBR is coming soon. Work is also ongoing to improve its stabil
information on zipf's law
Zipf’s law, named after the Harvard linguistic professor George Kingsley Zipf (1902-1950), is the observation that the frequency of occurrence of some event ( P ), as a function of the rank ( i) when the rank is determined by the above frequency of occurrence, is a power-law function Pi ~ 1/ia with the exponent a close to unity (1). Zipf’s law is a statistical observation that describes the freque
Netcraft
Resources Explore thought leadership, industry insights, and other resources related to cybercrime detection, disruption, and takedowns. Blog June 2024 Web Server Survey In the June 2024 survey we received responses from 1,101,431,853 sites across 269,118,919 domains and 12,865,432 web-facing computers. This reflects ... Read More Learn More Blog Too good to be true: Beware the temptation of recov
FESI Java library
Creating an interpreter The simplest example (listed below) is in SimpleIntrp.java in the directory examples/jslib. You can create an interpreter simply following this pattern: import java.io.*; import FESI.jslib.*; public class SimpleIntrp { public static void main(String args[]) { // Create the interpreter JSGlobalObject global = null; try { global = JSUtil.makeEvaluator(); } catch (JSEx
Computational Infrastructure for Operations Research Home Page
The Open Source Initiative explains it well. When people can read, redistribute, and modify the source code, software evolves. People improve it, people adapt it, people fix bugs. The results of open-source development have been remarkable. Community-based efforts to develop software under open-source licenses have produced high-quality, high-performance code on which much of the Internet is run.
The Borealis Project
Borealis is a distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Borealis builds on our previous efforts in the area of stream processing: Aurora and Medusa. The Borealis project is no longer an active research project. The last two releases of Borealis are: Download the Summer 2008 release of the Borealis software. Download the Winter 2
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Uppsala University Linear Road Implementations
Linux/RK
WinFF
Stream Query Repository: Network Traffic Management
ATLaS: a Powerful Database Language and System Based on Simple Extensions of SQL
AMPL Optimization: Empowering Businesses and Institutions
IBM Documentation
Volatile Arrays in Java
Aurora Project Page