GitHub
GitLab
BitBucket
VS Code
Git
Treehouse
Pantheon
CodePen
Apache Storm
Apache Spark
Apache Flink
Qubole
Hadoop
Google BigQuery
Apache Kafka
Amazon Kinesis
GitHub Apache StormBased on our record, GitHub seems to be a lot more popular than Apache Storm. While we know about 2466 links to GitHub, we've tracked only 11 mentions of Apache Storm. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / about 3 hours ago
Import requests From bs4 import BeautifulSoup From datetime import datetime Def fetch_github_trending(): url = "https://github.com/trending?since=daily" response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') repos = [] for article in soup.select('article.Box-row'): repo_link = article.select_one('h2 a')['href'] stars_today =... - Source: dev.to / 1 day ago
Git clone https://github.com//.git /opt/app Cd /opt/app Docker build -t app . Docker run -d --name app --restart unless-stopped -p 8080:8080 app. - Source: dev.to / 5 days ago
The core of the ecosystem is the official open-source server hosted on GitHub. It is written in TypeScript and implements the full MCP specification. - Source: dev.to / 9 days ago
This is why the gate needs a trace it can trust, and why AgentLens is the other half of this workflow. agent-eval scores and gates the output; AgentLens captures the trace of how the agent got there โ every model call and tool step, the resolved inputs (not the templated ones), the raw outputs. That trace is exactly the unforgeable, agent-didn't-author substrate that Tier 1+2 need to score against. Without it,... - Source: dev.to / 10 days ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 3 years ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
VS Code - Build and debug modern web and cloud applications, by Microsoft
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
