Apache Hadoop vs. Jenkins

Apache Hadoop (and its subsequent add-ons) are well-suited to larger, unstructured data flows, such as aggregation of web traffic or advertising. Geospatial algorithms and their outputs are well-suited for this kind of aggregation as structuring that data is challenging, but leaving it unstructured and performing queries as-needed is a better fit for most business models. With the advent of data science, I would expect Hadoop fits a LOT of their initial outputs quite well.

Incentivized

Jenkins is a highly customizable CI/CD tool with excellent community support. One can use Jenkins to build and deploy monolith services to microservices with ease. It can handle multiple "builds" per agent simultaneously, but the process can be resource hungry, and you need some impressive specs server for that. With Jenkins, you can automate almost any task. Also, as it is an open source, we can save a load of money by not spending on enterprise CI/CD tools.

Incentivized

• HDFS is reliable and solid, and in my experience with it, there are very few problems using it
• Enterprise support from different vendors makes it easier to 'sell' inside an enterprise
• It provides High Scalability and Redundancy
• Horizontal scaling and distributed architecture

Incentivized

• Automated Builds: Jenkins is configured to monitor the version control system for new pull requests. Once a pull request is created, Jenkins automatically triggers a build process. It checks out the code, compiles it, and performs any necessary build steps specified in the configuration.
• Unit Testing: Jenkins runs the suite of unit tests defined for the project. These tests verify the functionality of individual components and catch any regressions or errors. If any unit tests fail, Jenkins marks the build as unsuccessful, and the developer is notified to fix the issues.
• Code Analysis: Jenkins integrates with code analysis tools like SonarQube or Checkstyle. It analyzes the code for quality, adherence to coding standards, and potential bugs or vulnerabilities. The results are reported back to the developer and the product review team for further inspection.

Incentivized

• Hadoop is a batch oriented processing framework, it lacks real time or stream processing.
• Hadoop's HDFS file system is not a POSIX compliant file system and does not work well with small files, especially smaller than the default block size.
• Hadoop cannot be used for running interactive jobs or analytics.

Incentivized

• Jenkins can be vulnerable to security issues due to its open-source nature and the availability of many third-party plugins. There have been instances where malicious plugins have been discovered, and these can pose a significant risk to organisations.
• Jenkins can require a significant amount of maintenance, particularly when dealing with plugin updates and compatibility issues. Maintaining a stable and up-to-date Jenkins instance can be a challenge for organisations with limited resources.
• Jenkins' reporting capabilities are limited, and it can be challenging to extract meaningful insights from the data that Jenkins provides.

Incentivized

Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free

We have a certain buy-in as we have made a lot of integrations and useful tools around jenkins, so it would cost us quite some time to change to another tool. Besides that, it is very versatile, and once you have things set up, it feels unnecessary to change tool. It is also a plus that it is open source.

Incentivized

Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.

Incentivized

Jenkins streamlines development and provides end to end automated integration and deployment. It even supports Docker and Kubernetes using which container instances can be managed effectively. It is easy to add documentation and apply role based access to files and services using Jenkins giving full control to the users. Any deviation can be easily tracked using the audit logs.

Incentivized

No, when we integrated this with GitHub, it becomes more easy and smart to manage and control our workforce. Our distributed workforce is now streamlined to a single bucket. All of our codes and production outputs are now automatically synced with all the workers. There are many cases when our in-house team makes changes in the release, our remote workers make another release with other environment variables. So it is better to get all of the work in control.

Incentivized

We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.

Incentivized

As with all open source solutions, the support can be minimal and the information that you can find online can at times be misleading. Support may be one of the only real downsides to the overall software package. The user community can be helpful and is needed as the product is not the most user-friendly thing we have used.

Incentivized

Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.

It is worth well the time to setup Jenkins in a docker container. It is also well worth to take the time to move any "Jenkins configuration" into Jenkinsfiles and not take shortcuts.

Incentivized

I feel that this is a highly reliable and scalable solution computing technology that is highly capable of processing large data sets across multiple servers and thousands of machines in a well-defined and distributed manner. Apache Hadoop can automatically scale up the number of servers and machines that are needed to process, store, and analyze data sets. It also handles explosions in data with big data technology. Apache Hadoop is good at handling all node failures as well.

Incentivized

Overall, Jenkins is the easiest platform for someone who has no experience to come in and use effectively. We can get a junior engineer into Jenkins, give them access, and point them in the right direction with minimal hand-holding. The competing products I have used (TravisCI/GitLab/Azure) provide other options but can obfuscate the process due to the lack of straightforward simplicity. In other areas (capability, power, customization), Jenkins keeps up with the competition and, in some areas, like customization, exceeds others.

Incentivized

• As it was open source makes it popular choice for handling large chuck of datasets
• It was free earlier but now it’s licensed but still enterprise is a fine tuned version which makes it easier for new users and administrators to use it
• Our investment is worth every single penny.
• Initial cost is more as you might need to hire administrators to setup the cluster and make them in scalable. But once done it’s pretty easy

Incentivized

• We run about 30 test projects through Jenkins every day, multiple times a day; this allows us to focus on new tests rather than manually running all these tests.
• We rely heavily on reporting capabilities and email notifications; we have some jobs that send emails every time they run so we know if there is an issue with any of our services.

Incentivized