GitHub
GitLab
BitBucket
VS Code
Git
Treehouse
Pantheon
CodePen
Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Qubole
Snowflake
HortonWorks Data Platform
Databricks
GitHubAmazon EMR is recommended for data engineers, data scientists, and IT professionals who need to manage and process large datasets in a scalable, efficient, and cost-effective manner. It is especially suitable for businesses that are already using AWS services and want to leverage a tightly integrated ecosystem. Additionally, it is a good choice for organizations that require rapid and flexible data analysis capabilities provided by frameworks such as Hadoop, Spark, HBase, and Presto.
GitHub is an essential platform for modern software development. It makes it easy to host, manage, and collaborate on code while providing powerful tools for version control, project management, and team collaboration. Its large open-source community is another major strength, offering developers access to countless projects, resources, and opportunities to learn. Overall, GitHub is a reliable and professional platform that has become a fundamental part of the developer ecosystem.
Based on our record, GitHub seems to be a lot more popular than Amazon EMR. While we know about 2483 links to GitHub, we've tracked only 10 mentions of Amazon EMR. 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.
1228 push attempts died with fatal: could not read Username for 'https://github.com' — an https remote with no credential helper and no stored Credentials. First one 2026-07-21T20:48:03Z, still failing as I write this. Thirty-nine Days. - Source: dev.to / 5 days ago
They can include the protocol, it’s that regardless of what’s put in there it’ll use https, which is explained with examples both in the following sentences and then in more detail in a linked doc. > For repositories on GitHub, GitLab, and Bitbucket, a specifier now names a repository rather than choosing a transport. github:owner/repo, owner/repo, git+https://…, and git+ssh://git@… all resolve through the host's... - Source: Hacker News / 8 days ago
First things first, and this case, we had to understand what git and git hub really is. From the lesson, Git is basically a version control systems installed on the computer that tracks changes made within a project. On the other hand, git hub refers to an online platform allowing users to store their git repositories and this could be easily accessed through [https://github.com/]. Apart from just storing... - Source: dev.to / 7 days ago
[credential] useHttpPath = true [credential "https://github.com/"] helper = helper = "!f() { \ [ \"$1\" = get ] || exit 0; \ account=''; \ while IFS='=' read -r k v; do \ [ \"$k\" = path ] && account=${v%%/*}; \ done; \ [ -n \"$account\" ] || exit 0; \ token=$(gh auth token --user \"$account\") || exit 0; \ printf... - Source: dev.to / 9 days ago
This has now created our repository. This repository contains a link which we can share to other users, and this is the link that we need to link our local folder with the newly created repository. To do this, simply access it once you scroll down in the page you are in the simply copy the http link. This is what we shall use. The link usually looks like this http://github.com//. - Source: dev.to / 11 days ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 3 years ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: about 4 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: over 4 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / almost 5 years ago
Check out https://aws.amazon.com/emr/. Source: over 4 years ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
VS Code - Build and debug modern web and cloud applications, by Microsoft
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
