IT environments are more complex than ever before: the average organization now has 163 terabytes of information and runs dozens or hundreds of software applications. To manage this growing complexity and gain more control over their enterprise technology, businesses rely on data integration approaches such as extract, transfer, load (ETL) and integration platform as a service (iPaaS).
What’s the difference between ETL and iPaaS? While both iPaaS and ETL can be very effective data integration methods, there are some important differences between the two that potential users need to know.
In this article, we’ll clarify the question of iPaaS vs. ETL in terms of their differences, benefits, challenges, and use cases.
What is ETL?
ETL is a frequently used data integration method that pulls data from multiple sources and stores it in a target database. This target database is usually a data warehouse — a centralized data repository that has been optimized for business intelligence and reporting.
In ETL, data is extracted from source locations (potentially both internal and third-party sources), then transformed from its initial format in order to fit the standards and schema of the target database, before finally being loaded.
A variant of ETL — ELT (extract, load, transform) — switches the order of these processes around: data is loaded into the target database before being transformed. The ELT approach is typically better suited for NoSQL databases and handling unstructured data.
How Is iPaaS Different From ETL?
iPaaS is a class of all-in-one data integration technologies that is sometimes referred to as the “successor” of ETL. The first iPaaS was launched by Boomi in 2008.
The popularity of iPaaS owes largely to the rise of cloud computing, including cloud storage and software as a service (SaaS) offerings. Although iPaaS is often provisioned as a cloud service, it can also run on-premises and integrate data and applications in both environments.
iPaaS can run ETL workloads but can also enhance the feature set of ETL tools in many respects. For example, iPaaS is often low-code, making it accessible to users outside the IT departments. An iPaaS offering may also include support for a variety of integration patterns and use cases, such as Internet of Things (IoT), blockchain, and edge computing.
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Benefits and Challenges of ETL
The three greatest benefits of ETL are:
- Ease of integration: ETL is light-years ahead of manual data integration. Once your workflow is built, ETL processes can automatically collect, standardize, and store data within an enterprise data warehouse, making it easier to run queries and find hidden insights.
- Higher data quality: ETL processes allow you to define preset transformation rules and standards, ensuring that your data is always clean and consistent.
- Stability and predictability: ETL has been around for decades, which has made most ETL tools highly repeatable and predictable. This is especially valuable for large organizations that need to prove compliance with data laws and regulations.
The three biggest challenges of ETL are:
- Batch-driven, not real-time: ETL moves data in batches, usually on an hourly or daily basis. This can be too slow for fast-paced organizations that need real-time or near real-time information.
- Data only: ETL processes can only integrate data, not the applications that generate this data. This may not provide a tight enough integration for organizations that want ultimate oversight and control of their environment.
- Legacy-oriented: Many ETL tools exclusively work with, or are oriented towards, legacy on-premises systems. This can be inadequate for today’s cloud-centric IT workloads.
iPaaS addresses many of the shortcomings of ETL. ETL requires predictability, whereas iPaaS thrives on fluidity, flexibility, and real-time insights. iPaaS can integrate multiple systems and APIs, as well as data, and the origins of iPaaS as a cloud-native integration tool make it ideally suited for cloud, on-premises, and hybrid IT environments.
ETL vs. iPaaS: Final Thoughts
Both ETL and iPaaS have features and use cases that can make each the better choice for certain situations. However, many forward-thinking organizations — especially younger ones with an eye on the cloud — are turning to iPaaS for their data integration needs.
Are you considering iPaaS for your business? Get our guide to the 5 Must-Have Capabilities in a Modern iPaaS