Chen Cuello
NOV 6, 2023
5 min read
Don’t miss a thing!
You can unsubscribe anytime

In today’s business climate, where information is a valuable resource, companies and businesses must ensure an uncomplicated way to access their data warehouses at any time, from anywhere. Individual business teams or departments within those companies may store their collective data in different applications. Without a data integration solution, that information may remain unused.

Data integration tools gather information from different sources and compile it into various systems so it can later be presented in a unified manner. That process aims to ensure that data coming from multiple sources is funneled into one place and ready to use. It is essential for companies that regularly make data-based business decisions.

Currently, the two main solutions implemented by companies to combine all of that information into a single view are iPaaS and Reverse ETL. Both offer unique functionalities and benefits.

This article will help you resolve the dilemma of Reverse ETL vs. iPaaS and decide which one best fits your needs.

iPaaS: What You Need to Know

Integration Platform as a Service (iPaaS) is a cloud-based solution that helps entities integrate data between applications and sources. It’s a low-code or no-code platform that makes it easy to migrate data and processes between separate systems. Usually, iPaaS packages include pre-built connectors and other tool kits, meaning the users don’t need programming knowledge.

Once an iPaaS is connected to the company’s system, it uses API endpoints to allow teams operating different tools to access the same information by creating point-to-point data pipelines. It supports various data types and integration scenarios, and centralizing the data saves valuable time usually spent switching from one app to another.

iPaaS is used for different data integration tasks, such as:

  • Connecting on-premises systems to cloud applications
  • Automating data transfers between different tools and applications
  • Integrating data from multiple sources into a singular data warehouse
  • Building and managing real-time data pipelines

Reverse ETL: An Overview

Reverse ETL is the process of extracting data from a central storage system, like a data warehouse or data lake, and forwarding it to different operational tools that the company’s various teams use daily. This process makes the stored data operational and ready to use in third-party applications.

Implementing Reverse ETL eliminates the creation of data silos by allowing all users to have access to the stored information in real-time. That improves data visibility and team collaboration across the organization. Reverse ETL is commonly used for a variety of business purposes, such as:

  • More personalized customer experiences
  • Optimizing and automating marketing campaigns
  • Improving the overall sales performance
  • Optimizing operational efficiency and data accuracy

For example, a company can synchronize its CRM system with various platforms that analyze its sales data and allow the sales team real-life insight into the spending patterns and behaviors of the consumer base. That makes it easier to identify current market demands and make data-driven decisions. They can even loop in the marketing department to create targeted and effective marketing campaigns.

iPaaS vs. Reverse ETL: A Simplified Comparison

While both solutions help businesses better manage and integrate their data, they are significantly different from each other and offer unique benefits and functionalities. Even if some overlap is possible, both platforms are designed to perform different tasks.

For instance, migrating data from one CRM system to another is a simple point-to-point workflow and can be easily accomplished with iPaaS. The data is transferred using one API pipeline. But things get a little more complicated if you want to forward that data to other tools like SaaS applications or customer service software. We recommend using Reverse ETL in this instance to create a centralized point of truth and sync the information with all users.

If you’re still unsure of what each platform offers, below is a simple Reverse ETL and iPaaS comparison highlighting their advantages and disadvantages.

iPaaSReverse ETL
Business users can easily learn to use itBuilding more involved workflows requires knowledge of APIsThe data is taken from a single source of truthBuilding a proprietary in-house Reverse ETL platform is a complicated and long process
It has a visual interface for self-serveMistakes are easily made, and debugging can be trickyIt’s scalable to accommodate a larger volume of operations as the company growsSome knowledge of coding is required
It’s very affordable for companies operating on a smaller scaleLarger-scale integration becomes a costly affairIt supports continuous syncing, so the data is always up-to-dateIt may not be suitable for smaller businesses and companies
Supports a wide range of integrationsDoesn’t have a singular data warehouseStreamlines data governance for faster acquisition of informationA significant initial investment, depending on how many tool kits your operations require
The platform is highly customizableIt doesn’t allow end-to-end automationData lineage is clearly visible and traceable to facilitate necessary corrections


Assessing Your Data Needs

When deciding between reverse ETL vs iPaaS, you must first evaluate the specific data integration requirements of your business. Some crucial things to think about are:

  • Your goals and objectives – Be clear with what you want the result to be. That will help you better determine what data you need to integrate and where to start.
  • Quality of existing data – Check if the data you need to integrate is correct, complete, consistent, up-to-date, and unique. All of these things must be corrected to build a centralized data source with good data posture.
  • Data sources that need integration – Identify all systems and applications that contain data that must be combined into a centralized source, such as customer relationship management systems, enterprise resource planning systems, marketing automation platforms, emailing lists, etc.
  • The volume and complexity of data – To properly determine your data integration requirements, you must first assess the amount of data you have available, the number of data sources, and the complexity of the data transformation needed.
  • The final data integration destinations – This includes all systems and applications where you need to make the combined data available, such as business intelligence (BI) platforms, data warehouses and data lakes, operational systems, and go-to-market applications.

How to Choose the Right Solution

Once you’ve assessed your needs internally, it’s time to evaluate the different data integration solutions. Making the right choice will impact your business operations, so to get on the right track, answer the below question:

  • Data Architecture Is your actionable information centralized in one source of truth, and is that something you plan to implement?
  • Ease of Use – Is the integration tool user-friendly? Does it require some coding knowledge, or is it self-serve?
  • Scalability – Can the solution scale up with the growth of your business to handle an increased number of go-to-market applications?
  • Features – Does the solution have all of the necessary tools and functionalities that your business needs regarding data integration?
  • Use cases – How will the integration tool be used the most?
  • Observability – Can the system be easily customized to better fit your needs or easily modified in case of errors?
  • Security – Does the solution offer the necessary level of security to protect your data from possible threats?
  • Budget – Will you need to pay additional costs as your data integration needs grow?

Rivery in Action

iPaaS and Reverese ETL are not new additions to the IT sphere. They are tried-and-tested solutions that have transformed how many established and up-and-coming companies handle and process their data. There are many real-life case studies that showcase the results.

A notable example is Bayer, a German pharmaceutical giant that needed assistance to integrate its data more effectively. The challenge was the sheer volume of sources which Bayer was pulling its information from. Standard integration solutions were no longer cutting it, so the company implemented Rivery, and within six months, it connected to 30% more sources. Now, it can transfer that data into Snowflake and then plug it into other marketing sources.

Another interesting case study is Minute Media, a tech-based media company with six other publications globally. It needed to centralize its 60+ data sources into a unified data hub and use that information to generate ROI reports for its clients and partners. They completely integrated all sources and automated the data integration and reporting processes. Now, they have a flexible ecosystem that can scale up alongside the company.

However, these data integration solutions are applicable at a much smaller scale as well. A newly launched health-food brand was developing a data-based strategy but needed a scalable infrastructure to match its projected growth. They decided on an off-the-shelf solution that allowed them to instantly connect to their sources with no coding needed. An additional bonus is the built-in data security and regulation compliance.

These are all actual case studies taken from Rivery, a leading data management platform that offers SaaS ELT data integration services. The benefits of using this provider are self-evident in the end results, but if this has piqued your interest, there are many more reviews from satisfied customers on their website.


iPaaS and Reverse ETL are powerful and efficient data integration solutions. Users can benefit from unique benefits and functionalities differently, depending on their specific needs and project goals. iPaaS is perfect for smaller-scale point-to-point data integration, while Reverse ETL helps the data stored in a centralized hub become actionable information.

Both have their place in today’s business market, but to implement the right one, businesses and companies must first assess their specific data needs and business goals.

Minimize the firefighting.
Maximize ROI on pipelines.

icon icon