ETL (extract, transform, load) is the powerhouse of modern business intelligence and analytics. The ETL process efficiently integrates data from a wide range of sources including files, databases, and APIs. It then transforms that data as necessary before loading it into the target data warehouse.

Since its appearance in the 1970s, ETL has been conducted mostly on-premises, i.e. using the organization’s own hardware and IT infrastructure. The rise of cloud computing, however, has significantly changed this paradigm. According to a 2018 study by IT research company Forrester, 51 percent of large enterprises are running complex data analyses in the cloud. What’s more, Forrester predicts that by 2021, this figure will rise to 61 percent, while just 44 percent of companies will be doing analytics on-premises.

Given this shift to the cloud, it’s no surprise that many organizations are looking for cloud-native ETL solutions to complement their new IT environments. But what is cloud-native ETL exactly, and what are the benefits of cloud-native ETL solutions?

Table of Contents

  1. What is Cloud-Native ETL?
  2. From On-Premises to Cloud-Native ETL
  3. Cloud-Native ETL Architecture
  4. Why Choose for Cloud-Native ETL?

What is Cloud-Native ETL?

“Cloud-native ETL” refers to ETL tools and processes specifically designed to take advantage of cloud computing, as opposed to on-premises infrastructure. The benefits of the cloud include:

  • Scalable: Cloud computing is significantly more scalable than on-premises. If you hit the limits of storage or compute power in the cloud, you can easily provision another server or CPU. With on-premises computing, however, you’ll need to purchase more hardware yourself, which can be both costly and time-consuming.
  • Mobile-friendly: Cloud services are usually compatible with devices such as smartphones, tablets, and laptops so that users can access them from anywhere, at any time. On-premises ETL can be reconfigured to be mobile-friendly but usually doesn’t come with this functionality out of the box.
  • Fully managed: Public cloud providers offer fully managed solutions for the convenience of the end-user: they abstract away the technical details and also deal with support and maintenance obligations. Using an on-premises ETL solution means that you’ll have to handle these concerns yourself, which often necessitates hiring skilled in-house tech staff.

Cloud-native ETL tools have been created with these advantages (and more) in mind. Although most of the ETL process remains the same as on-premises, behind the scenes your ETL workloads are now running on a remote server, instead of in an IT closet somewhere nearby.

From On-Premises to Cloud-Native ETL

As previously stated, cloud-native ETL solutions are gaining in popularity. So why, and how, do organizations move ETL from on-premises to the cloud? The factors to consider when looking at a cloud-native ETL solution include:

  • Speed: If speed is a primary concern for you, then you may be better off using an on-premises ETL solution. While ETL in the cloud can be very fast, it can also suffer from latency issues, especially if the cloud servers are located in a different geographical region. On the other hand, if your business is already scattered across multiple locations, some degree of latency may be expected and tolerable.
  • Cybersecurity: Both cloud and on-premises ETL solutions can be made secure. The winner here depends on what you’re looking for. 61 percent of chief information security officers (CISOs) believe that the cloud is as safe or safer than an on-premises solution. However, on-premises ETL may be necessary if you have data that cannot be handled by a third party according to laws and regulations (e.g. healthcare data, financial data, payment card information, etc.).
  • Reliability: When cloud services go down, it’s not your responsibility to fix it. This might be the biggest selling point of all for your IT support staff, who don’t want to wake up in the middle of the night to go fix an urgent issue with on-premises hardware. Your cloud vendor should give you an SLA (service level agreement) stating the level of uptime that you can expect. For example, the AWS Glue cloud-native ETL solution guarantees monthly uptime of 99.9 percent, which translates to roughly 44 minutes of outages per month.

Even if you use a cloud-native ETL tool, that doesn’t mean that your entire ETL workflow has to move to the cloud. Many organizations use a “hybrid” ETL model in which some of their data and processes remain on-premises, as best fits their needs.

Cloud-Native ETL Architecture

Traditional on-premises ETL tools have their place, but more and more organizations are viewing them as too sluggish, inflexible, and costly for their modern data-driven needs. It’s in this competitive, constantly evolving business landscape that cloud-native ETL tools have emerged as the leading choice.

With all that said, what does a cloud-native ETL tool actually look like? The answer will depend on which ETL tool you use. Some cloud-native ETL solutions are virtually indistinguishable from their on-premises counterparts, while others take advantage of the cloud environment in which they run.

Apache Hadoop is an example of a big data processing framework that is a good fit for any cloud-native ETL architecture. By distributing and processing data across multiple clusters in different locations, Hadoop is able to take advantage of parallelism and redundancy. Hadoop is powered by MapReduce, a programming model that splits large datasets into independent chunks and performs operations on them.

To help incorporate Hadoop as part of your ETL architecture, cloud-native ETL tools like are able to access data on any Hadoop Distributed File System (HDFS). Hadoop is just one benefit for cloud-native ETL tools that can’t be replicated in on-premises ETL.

In addition, cloud-native ETL solutions give you greater choice and more flexibility over your ETL architecture:

  • With cloud-native ETL, you can use both on-premises and cloud data warehouses as the target of your ETL pipeline. This includes leading cloud data warehouse solutions such as Amazon RedshiftGoogle BigQuery, and Snowflake.
  • For organizations that require truly up-to-the-minute insights, cloud-native ETL is better for processing real-time and streaming data.
  • The move from on-premises to the cloud has also initiated a shift from ETL to other data integration solutions, such as ELT (extract, load, transform). In the ELT pipeline, data is first loaded into the target repository before performing any transformations. ELT is better suited for the cloud, thanks in large part to the scalability and flexibility of cloud computing. In particular, unlike ETL, ELT can have either a cloud data warehouse or a data lake as its destination. Data lakes are information stores that may contain both structured and unstructured data in their native raw format (as opposed to data warehouses, which only store structured data).

Why Choose for Cloud-Native ETL? is an enterprise-grade, cloud-native, industry-leading data integration platform. With more than 100 pre-built integrations and a simple visual drag-and-drop interface, makes it easy for even non-technical users to build powerful, robust pipelines to a target data warehouse.

As a cloud-native ETL (and ELT) solution, offers the following benefits:

  • Elasticity and scalability: The platform handles all of the complex technical issues behind the scenes: deployments, logging and monitoring, job scheduling, data security, and maintenance. This frees you up to focus on what really matters: the BI and analytics insights that a strong cloud-native ETL tool enables.
  • Rich feature set: is for everyone from ETL newbies to seasoned professionals, and we have the feature set to prove it. For example,’s workflow engine allows users to orchestrate and schedule the execution of data pipelines at the times most convenient to you, so key decision-makers can always enjoy up-to-the-minute insights. also comes with its own expression language for advanced users to implement complex data preparation tasks. 
  • Support: Even with cloud-native ETL solutions, data integration can be challenging: you need to deal with questions such as performance, connectors and integrations, different file formats, and much more. offers email, phone, chat, and online meeting support so that you can always get the help and answers you need.

Want to learn more about how's cloud-native ETL tool can enhance your data integration workflows? Get in touch with our team today for a chat about your needs and a free trial of the platform.