Using An ETL Platform VS Writing Your Own Code

The Advantages of Using an ETL Platform vs Writing Your Own Code

What if we told you that you don’t have to write your own ETL code? Would you raise an eyebrow or jump out of your chair with joy? Whether you know it or not, various ETL platforms out there let you develop ETL processes on the cloud without writing a single line of code (yes, Xplenty is one of them). However, not everybody is ready to jump on the ETL platform bandwagon because they believe they have a lot to lose if they stop coding their own ETL processes. Is there? Let’s compare the two methods of development and see.

Ease of Use

Writing your own ETL code is not that trivial for everyone. Sure, developers may speak fluent Pythonese, Javanese or some other programming language, and they might prefer reading some code instead of handling a user interface. However, what starts out as a simple ETL process can get more complex over time. So does the coding, which eventually becomes less manageable. You know how it is: it always starts out as a lovely short story, but eventually it becomes a big, convoluted volume that rivals Tolstoy’s "War & Peace."

ETL platforms are naturally much easier to manage than writing your own code. They allow non-coders to design and execute ETL processes, and they give coders a visual view of ETL processes via ETL flows. These flows are self-descriptive, so coders don’t require any extra comments to grasp them. Therefore, it’s easier to review and change the ETL process on an ETL platform instead of dealing with monstrous code, especially over a long period of time.

We say: Although it’s tempting to code your own ETL process, it will eventually become really difficult. ETL platforms keep the ETL process under wraps.


All developers know that maintaining ETL code sucks. Depending on the developer who wrote it, it could be in SQL, Java, Python, Pig, or another language. It could be well structured and highly organized, but then again it might not. If you need to fix bugs, perform optimizations, or even change the ETL process, someone’s going to wind up with a few headaches; version management and upgrades are an entirely different story.

Maintenance is a no-brainer on ETL platforms. Changes are easy to implement, and they don’t require coding skills. Nonetheless, if you are a control freak who prefers to manage everything yourself even though it’s not comfortable, you’ll keep writing your own code.

We say: ETL platforms require little maintenance. Control freaks will keep writing their own code.


Coding your own ETL can be a huge benefit when it comes to optimizations. If you have an intimate knowledge of your data and the ETL process and you have an expert data engineer on board, you can really fine-tune your ETL process to run as smoothly as possible.

However, we all know that finding elite data engineers is as difficult as finding a solitary panda in a bamboo forest. Your average developer may code an ETL process in a sloppy way, whereas an ETL platform could achieve better results. In fact, some of our clients who tried our ETL platform saw their processes running twice as fast compared to their own code.

We say: Your own ETL code will perform better if you’re a l33t data engineer. However, ETL platforms could produce quicker results than those given by your average developer.


If you write your own ETL code, you have to make sure everything is nice and neat. You need to generate well-formatted logs, handle exceptions and errors, and store everything in one well-organized repository.

ETL platforms take care of all that for you—everything is automatically nice and organized.

We say: ETL platforms are more organized than writing your own code.


Your ETL code may or may not be scalable, depending on which framework you use. The same applies if you use an ETL platform because it also relies on a framework—whether it’s Hadoop, Spark, or another open-source or commercial solution.

It’s important to make sure that your framework scales out rather than up. In other words, make sure you can easily add more nodes to the cluster rather than having to upgrade a single machine. No matter how big your budget is, one machine will always have a silicone ceiling when it comes to adding more memory and CPU. This leads to problems as your data keeps growing. So, whether you code your own ETL or use an ETL platform, make sure you can scale out.

We say: In both cases, scaling depends on the framework. Just make sure you can scale up.

Workflow Management

Designing workflows is an important part of your ETL process. Too many developers code workflows themselves, which requires even more work and maintenance. It’s better to use a workflow management framework like Luigi, but even that option requires some coding and maintenance.

ETL platforms provide workflow management that’s much easier to use, usually via a point-and-click interface. There’s no need to manage any framework when development and maintenance is a whole lot simpler.

We say: ETL platforms provide easier workflow management.


You need an ETL developer to write your own ETL code. You hire one full time for about $95,000 per year. You’ll probably use an open-source framework because it doesn’t require any additional expenses.

Costs vary when it comes to ETL platforms. Xplenty’s data integration platform keeps ETL costs considerably low, with a free trial (and free sandbox to play in) and plans starting at only a couple of hundred dollars a month.

We say: Using an ETL platform can decrease costs.


If you’re looking for flexibility, coding your own ETL is the way to go. If you write your own code, you can write complex transformations or unique algorithms that a graphical interface on an ETL platform just can’t provide. If your ETL or data processing requires this type of niche processing, flexibility is not just a benefit—it’s a necessity.

You can enjoy this advantage if your ETL platform lets you write your own code. Nonetheless, some ETL platforms only provide a graphical user interface with limited functions for data manipulation. This is great for the standard data processing, but it won’t do if you need a specific, highly customized ETL process.

We say: Writing your own code provides more flexibility.

Bottom Line

Using an ETL platform has plenty of advantages. ETL platforms are easier to use, become more manageable over time, need less maintenance, are better organized, may include simpler workflow management, and usually cost less.

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