GitKraken
SourceTree
GitHub Desktop
SmartGit
Tower
Fork
TortoiseGit
Git Extensions
Apache Pig
Looker
Jupyter
Google BigQuery
Presto DB
Databricks
Rakam
Informatica
GitKraken
Apache PigApache Pig is recommended for data engineers and analysts who are working in Apache Hadoop environments and need to perform ETL (Extract, Transform, Load) operations on large datasets. It is also suitable for teams looking to leverage existing Hadoop infrastructures without delving into complex Java MapReduce programming or when migrating legacy processing scripts based on Pig Latin.
Based on our record, GitKraken should be more popular than Apache Pig. It has been mentiond 4 times since March 2021. 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.
I'll have to try this out. I'm currently a huge GitKraken[1] fan. [1] https://gitkraken.com. - Source: Hacker News / over 1 year ago
The Git CLI is terrifying and awful. It's far too easy to clobber your own work -- and that of others -- when the whole point of it was to prevent that. While you still need to really deeply understand several git concepts to use it, GitKraken[0] is the best GUI tool I've used in daily practice. It integrates well with git hosts and has an attractive and mostly comprehensible interface. Accordingly, it isn't free... - Source: Hacker News / over 3 years ago
I like GitKraken partially because it was originally loosely based on the look/feel of Guitar Hero. Source: over 4 years ago
This experience was also invaluable because I had a walking fountain of knowledge sitting next to me and was really cool about answering my questions and pointing out all code style errors in countless PR reviews. I cannot count the amount of times he had to explain me the whole rebase workflow. What really helped me improve my Git knowledge was GitKraken and other similar tools. - Source: dev.to / over 4 years ago
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / almost 4 years ago
In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / almost 5 years ago
SourceTree - Mac and Windows client for Mercurial and Git.
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
GitHub Desktop - GitHub Desktop is a seamless way to contribute to projects on GitHub and GitHub Enterprise.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
SmartGit - SmartGit is a front-end for the distributed version control system Git and runs on Windows, Mac OS...
Google BigQuery - A fully managed data warehouse for large-scale data analytics.