Five differences between using an ETL platform vs. writing your own code:
- Writing your own code can be a long and laborious process that requires programming experience.
- You also need to consider ongoing maintenance and other issues when writing your own code.
- It can be difficult to scale pipelines when writing your own code for ETL.
- Using an ETL platform can simplify ETL processes and make it easier to build big data pipelines that integrate data such as e-commerce information.
- Not all ETL platforms are the same. Using an ETL platform like Integrate.io that integrates data quickly and securely is a much better fit for your business needs.
The ETL (extract, transform, load) process is one of the most critical, and one of the most challenging, parts of enterprise data integration. But what if we told you there was a low-code ETL solution to your problems?
Table of Contents:
- What is ETL?
- The Benefits of Using an ETL Platform
- Writing Your Own Code, Explained
- Using an ETL Platform vs. Manual ETL
- Using an ETL Platform vs Writing Your Own Code:
Integrate.io is the low-code/no-code data integration solution that makes life easy. There’s no complicated jargon or writing your own code. Just use the platform’s drag-and-drop interface and out-of-the-box integrations to move data from sources such as e-commerce systems to a centralized cloud data warehouse. You can also transfer data between locations using ELT, ReverseETL, and super-fast CDC. Want to know more about using an ETL platform? Contact Integrate.io to learn about a 7-day demo.
What is ETL?
ETL means the Extract, Transform, and Load process of collecting and synthesizing data. The process collects and processes data from various data sources into a single data store used for business intelligence analysis.
Traditionally, the ETL process has been hard-coded. Programmers set instructions to extract data from its source, transform it into a usable format for analytics, and load the transformed data into the appropriate target system such as a data warehouse.
Hard-coding data introduces a lot of problems, including ongoing maintenance, invalid or incorrect data, limited ability to blend datasets, inflexibility and in general, it’s just more expensive.
Luckily, some platforms, like Integrate.io, have introduced low-code data that removes these roadblocks as companies scale their data structure and perform more sophisticated data analysis for e-commerce and other functions. You can also use Integrate.io to execute other data integration methods such as Extract, Load, Transform (ELT), ReverseETL, and super-fast CDC.
The Benefits of Using an ETL Platform
The term “low-code ETL” refers to a software platform that builds ETL and data integration pipelines nearly automatically, requiring little or no input from developers. Low-code ETL platforms often run in the cloud and usually have a simple, drag-and-drop visual interface, allowing users to easily understand raw data that flows in and out of their organization.
Using low-code tools allows businesses to not only revamp their ETL process but also to move on to more sophisticated data transformations, like a data lake or data mart.
Low-code platforms like Integrate.io also improve data quality and make it easier to blend disparate data types when data warehousing into platforms like Amazon Redshift and Microsoft Azure.
Writing Your Own Code, Explained
The term “manual ETL” refers to the traditional way of performing ETL: writing your own code with the help of one or more ETL developers.
Manual ETL development requires a wide range of skills, including:
- Documenting requirements and outlining the ETL process when writing your own code.
- Creating models to describe the data extraction taking place during ETL.
- Formulating the architecture of the target data warehouse.
- Developing the data pipelines that transport information from source databases to the data warehouse.
- Testing the system and running regular performance checks when writing your own code.
Again, manual ETL has proven inefficient for organizations that rely heavily on large data sets to make decisions. Your ETL pipeline should be clean, uncomplicated, and flexible.
Using an ETL Platform vs. Manual ETL: Major Differences
Now that we’ve defined low-code ETL and manual ETL, let’s discuss the major differences between these two alternatives.
1. Ease of Use
Writing your own ETL code isn’t a trivial task, even for experienced developers. As discussed above, ETL development requires many different data science and data analytics skills, as well as in-depth knowledge of one or more complicated programming languages..
Low-code ETL platforms are by design much easier to use than a manually written codebase. Even non-technical employees can design and execute ETL processes and create data models, thanks to an intuitive user interface that provides a visual depiction of ETL data flows.
Let’s speak plainly: maintaining your ETL code manually sucks.
First, there’s the question of programming languages. ETL code could be in Java, SQL, Python, Apache Pig, or any number of alternatives. Second, your ETL code might be out-of-date or poorly maintained, creating a massive headache for anyone who tries to dive into the codebase. The situation couldn’t be more different for low-code ETL platforms, where maintenance is a no-brainer. You don’t need a degree in computer science in order to make changes in Integrate.io, for example—you can just use the straightforward, drag-and-drop user interface.
With Integrate.io, you no longer have to worry about writing your own code. Using an ETL platform like this solves data integration bottlenecks so you can focus on more important business tasks. Contact Integrate.io to learn about a 7-day demo.
Coding your own ETL can be a huge benefit in terms of performance optimization. If you have an expert data engineer on board who knows your ETL processes, you can optimize your ETL process to run as smoothly as possible.
Related Reading: How to Improve Your ETL Performance
Finding and training an expert ETL developer is both challenging and time-consuming. If you don’t have such a person already on staff, using a low-code ETL platform may produce higher-quality code than your average ETL developer.
Here at Integrate.io, for example, some of our clients reported that our low-code ETL platform generated code that ran twice as fast as their own codebase.
If you write your own ETL code, you have to make sure everything is nice and neat. For example, you need to generate well-formatted logs, handle exceptions and errors, and store everything in one well-organized repository.
Low-code ETL platforms eliminate all of these concerns for you. Using an ETL tool allows you to manage the different data flows using visual representation. This way, all members of your team can see the big picture about functions such as e-commerce as well as the smaller details without needing to understand code. An ETL tool also facilitates reusing logic without having to rewrite the same code multiple times, and schedules jobs in a way that controls the dependencies between the components in the data flow.
Related reading: 7 Ways to Reverse ETL
5. Using an ETL Platform vs. Writing Your Own Code: Scalability
Your manual ETL code may or may not be scalable, depending on which framework you use. However, the same is true if you use a low-code ETL platform, because it also relies on a framework—whether it’s Hadoop, Spark, or another open-source or commercial solution.
No matter how big your budget is, a single machine will always have a silicone ceiling when it comes to adding more memory and CPU. This will inevitably lead to problems. So whether you code your own ETL or use a low-code ETL platform, make sure you can scale out.
6. Workflow Management
Designing and managing workflows is an important part of the ETL process. Too many developers code workflows themselves, which requires a great deal of management and maintenance. Using a workflow management framework is a better alternative, but even this option needs some manual coding.
ETL platforms provide workflow management that’s much easier to use, usually via a straightforward point-and-click interface. There’s no need to manage any framework when development and maintenance is a whole lot simpler.
If you’re writing your own ETL code, hiring an ETL developer is an absolute must. According to the job search marketplace ZipRecruiter, the average full-time salary of an ETL developer in the U.S. is over $109.881, which is an expense many organizations can’t afford.
Manual ETL development may or may not require additional costs. If you use a free open-source framework such as Hadoop or Spark, you’ll be able to keep your expenses to a minimum.
Costs vary when it comes to low-code ETL platforms. Integrate.io’s ETL data integration platform keeps ETL costs lower than even the lowest developer salary. That’s because you pay for the number of data integrations you use and not the amount of data you consume, which differs from other ETL platforms. This innovative pricing model could save you cash in the long run.
Also, new Integrate.io users get a 7-day demo.
Related reading: Top 7 ETL Tools for 2022
If you’re looking for flexibility, coding your own ETL is the way to go. Manual ETL development, compared to using an ETL platform with a simple user interface, lets you write complex transformations and unique algorithms. If your ETL workflows require this type of niche data processing, flexibility isn’t just a benefit—it’s a must.
Still, you can enjoy the advantage of flexibility if your low-code ETL platform also lets you write your own code. Depending on the platform, some low-code ETL solutions may or may not let you perform custom data manipulations.
Using an ETL Platform vs. Writing Your Own Code
How Integrate.io Can Help
Using an ETL platform like Integrate.io takes the pain out of writing your own code. With its deep e-commerce capabilities, you can transfer data from disparate sources to a final destination like a data warehouse or lake and generate business intelligence that improves decision-making in your organization.
Integrate.io’s simple, cloud-based, drag-and-drop interface streamlines data integration. Choose from hundreds of out-of-the-box integrations and start building data pipelines instead of writing your own code from scratch.