GitLab vs. Hortonworks Data Platform

GitLab is good if you work a lot with code and do complex repository actions. It gives you a very good overview of what were the states of your branches and the files in them at different stages in time. It's also way easier and more efficient to write pipelines for CI\CD. It's easier to read and it's easier to write them. It takes fewer clicks to achieve the same things with GitLab than it does for competitor products.

Incentivized

I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.

Incentivized

• GitLab excels in managing code versions, allowing easy tracking of changes, branch management, and merging contributions.
• It helps maintain code stability and reliability, saving time and effort in the development or research workflow.
• Powerful code review features, enabling collaboration and feedback among team members.
• Robust project management features, including issue tracking, kanban boards, and milestones.

Incentivized

• It does a good job of packaging a lot of big data components into bundles and lets you use the ones you are interested in or need. It supports an extensive list of components which lets us solve many problems.
• It provides the ability to manage installations and maintenance using Apache Ambari. It helps us in using management packs to install/upgrade components easily. It also helps us add, remove components, add, remove hosts, perform upgrades in a convenient manner. It also provides alerts and notifications and monitors the environment.
• What they excel in is packaging open source components that are relevant and are useful to solve and complement each other as well as contribute to enhancing those components. They do a great job in the community to keep on top of what would be useful to users, fixing bugs and working with other companies and individuals to make the platform better.

Incentivized

• CI variables management is sometimes hard to use, for example, with File type variables. The scope of each variable is also hard to guess.
• Access Token: there are too many types (Personal, Project, global..), and it is hard to identify the scope and where it comes from once created.
• Runners: auto-scaled runners are for the moment hard to put in place, and monitoring is not easy.

Incentivized

• Since it doesn't come with propriety tools for big data management, additional integration is need (for query handling, search, etc).
• It was very straightforward to store clinical data without relations, such as data from sensors of a medical device. But it has limitations when needed to combine the data with other clinical data in structured format (e.g. lab results, diagnosis).
• Overall look and feel of front-end management tools (e.g. monitoring) are not good. It is not bad but it doesn't look professional.

Incentivized

I really feel the platform has matured quite faster than others, and it is always at the top of its game compared to the different vendors like GitHub, Azure pipelines, CircleCI, Travis, Jenkins. Since it provides, agents, CI/CD, repository hosting, Secrets management, user management, and Single Sign on; among other features

Incentivized

I find it easy to use, I haven't had to do the integration work, so that's why it is a 9/10, cause I can't speak to how easy that part was or the initial set up, but day to day use is great!

Incentivized

I've never had experienced outages from GItlab itself, but regarding the code I have deployed to Gitlab, the history helps a lot to trace the cause of the issue or performing a rollback to go back to a working version

Incentivized

GItlab reponsiveness is amazing, has never left me IDLE. I've never had issues even with complex projects. I have not experienced any issues when integrating it with agents for example or SSO

Incentivized

At this point, I do not have much experience with Gitlab support as I have never had to engage them. They have documentation that is helpful, not quite as extensive as other documentation, but helpful nonetheless. They also seem to be relatively responsive on social media platforms (twitter) and really thrived when GitHub was acquired by Microsoft

Incentivized

Try not to change variable names.

Incentivized

Gitlab seems more cutting-edge than GitHub; however, its AI tools are not yet as mature as those of CoPilot. It feels like the next-generation product, so as we selected a tool for our startup, we decided to invest in the disruptor in the space. While there are fewer out-of-the-box templates for Gitlab, we have never discovered a lack of feature parity.

Incentivized

We chose [Hortonworks Data Platform] because it's free and because [it] was an IBM partner, suggested as big data platform after biginsights platform.

You can install in more physical computer without high specs, then you can use it in order to learn how to deploy, configure a complete big data cluster.

We installed also in a cloud infrastructure of 5 virtual machine

Incentivized

I think is very well designed, and like any VCS it works as intended

Incentivized

• GitLab cut down our spent on container, package and infrastructure registry
• Best thing is we can now have everything in single platform which cost effective too
• Quality of support is really good and they do have emergency support team as well which is great

Incentivized

• It is difficult to have a negative impact, because the required investment is not that high.
• The big open community behind Hortonworks and related Apache Project makes it easy to put 'the wheel to meet the road' quite quickly.
• We have seen management meetings where the attendants were impressed by the results achieved with the datalake built on HDP.

Incentivized