By efficiently moving data from source to target locations, ETL (extract, transform, load) is the powerhouse of enterprise data integration. ETL helps every department in your organization, from sales and marketing to finance and customer support, get the unique insights it needs to make smarter data-driven business decisions.
Yet with all that said, how do you pick an ETL tool in the first place? In this article, we’ll discuss 8 criteria for evaluating an ETL tool, as well as how some of the best ETL tools stack up according to these criteria.
Perhaps the most important question when evaluating an ETL tool is: does it offer the necessary pre-built integrations and connectors for your data sources?
Trying to manually build a connector to your data, whether in files, databases, websites, or SaaS applications, can be a highly technical and time-intensive endeavor. This means that choosing the right ETL tool with pre-built integrations for your data sources can save you anywhere from hours to weeks of work.
Note that as your business needs change, your ETL pipeline may need to evolve along with them. By looking for a flexible ETL solution that includes a wide range of connectors and integrations, it will be easier to adapt to any changes in the future.
Some ETL tools are intended only for technical experts, while others are open to even non-technical business users. While both options have their pros and cons, it’s important to be aware of which one better fits your situation.
The IT research and advisory firm Gartner has written about the importance of “citizen data scientists” : people who make use of advanced data science capabilities to deliver insightful reports and cutting-edge discoveries, but who aren’t experts in the field themselves. Picking an ETL solution that’s easy to use—for example, one that has a simple drag-and-drop interface—will open the tool up to more people and help citizen data scientists participate in the ETL process.
Features such as an ETL tool’s connectors and learning curve are tremendously valuable. But that’s not worth much if it doesn’t fit in your budget in the first place. As with the user-friendliness criterion, there’s a wide range of options to choose from here, from tools that are free and open-source to pricey software licenses that cost hundreds or thousands of dollars per month.
Some ETL tools charge a flat monthly or annual fee, while others charge based on usage (e.g. the number of CPU hours, or the number of data rows per month included in your ETL pipeline). Take stock of how many users you expect to have, and how you plan to use the tool, to see which options are most cost-effective for you.
If you’re processing massive quantities of data on a regular basis, the scalability and performance of your ETL tool should be a primary concern. The best ETL tools are able to scale both up and down to meet your needs, as the current situation requires.
In 2016, IDC found that the average company was managing 163 terabytes (163,000 gigabytes) of information. This sizable amount almost certainly looms larger now, since data tends to accumulate over time. This highlights the importance of choosing a scalable, high-performance ETL tool that can grow alongside your business.
It’s almost a guarantee that you’ll have a question or problem while using your ETL tool, from minor performance issues to bugs that bring down the entire system. When disaster strikes, will you be able to get the help you need in a timely and professional manner?
ETL tools (and software in general) may offer several options for customer support, from phone, chat, and email support to manuals, FAQs, knowledge bases, and user forums. Some may only have free support, while others may have a tiered paid support system in which higher tiers enjoy more personalized attention. Do your research to see what your prospective options have to offer in terms of support, and decide if they work well for you.
Businesses that handle sensitive and confidential data, especially personally identifiable information (PII), have an obligation to protect this data both in transit and at rest, keeping it away from malicious actors. This isn’t just a moral question, of course—it’s also a legal issue that can put you on the wrong side of regulations such as GDPR and HIPAA if you suffer a data breach.
if you’re in an industry such as healthcare, finance, or retail that processes sensitive information, it’s your obligation to choose an ETL tool that can encrypt this data. Even if encrypted information falls into the wrong hands, it will be little more than gibberish without the right decryption key, which adds an extra level of security to your ETL workflow.
--> Our NewsletterBatch processing is the traditional method of doing ETL: Data is processed in batches at regular intervals, usually according to a defined schedule, and uplifted into the target data warehouse. Using batch processing is efficient because it helps to reduce I/O events and network bandwidth, but it also results in slower insights, since ETL only runs at certain intervals.
In recent years, however, some businesses have been adopting fast batch or real-time ETL, where data is sent through the ETL pipeline nearly instantaneously, allowing end-users to benefit from up-to-the-minute insights. Real-time ETL processing can be valuable for use cases such as fraud detection and IT security, in which every minute counts.
ELT (extract, load, transform) is a variant of ETL in which data is first loaded into the target data warehouse or data lake before being transformed in place. This process is often better suited for unstructured, semi-structured, and raw data that you want to store in its original format.
Because ELT is a much newer technology than ETL, there are fewer tools available, making it harder to develop an ELT pipeline. In addition, standard ELT may violate data security regulations such as GDPR and HIPAA, which require you to redact sensitive information before uploading it to the cloud. Make sure you fully understand the consequences of this alternative before switching to ELT and looking for an ELT tool.
The 8 ETL tool criteria above offer a comprehensive (although not exhaustive) set of ways for you to judge and compare ETL tools. In the next few sections, we’ll discuss how you can use these criteria to evaluate some of the best ETL tools on the market right now.
Integrate.io is a feature-rich ETL and data integration platform that makes it easy to build robust ETL data pipelines in the cloud. Here’s how Integrate.io stacks up according to the criteria for ETL tools:
Integrate.io has a wide variety of use cases, thanks to the tool’s pre-built connectors, the gentle learning curve, the scalable platform, and the choice between ETL and ELT pipelines. Everything from simple replication to complex data preparation and transformation tasks is possible with Integrate.io.
Stitch is a cloud-first, open-source data integration platform. Here’s how Stitch compares based on the criteria above:
The most distinguishing feature about Stitch is that it’s an ELT-only tool, which makes it ideal for certain use cases and entirely inappropriate for others. ELT is often more flexible and offers a faster time to value, but isn’t right for every situation.
Fivetran is an automated data integration tool that can load information into cloud data warehouses such as Amazon Redshift, Google BigQuery, Microsoft Azure, and Snowflake. Here’s how Fivetran compares:
As another ELT tool, Fivetran is an interesting option for users who want an alternative to traditional ETL. Fivetran is likely best for organizations with simple, low-volume ETL requirements, as well as SQL experts who can code up custom data transformations.
Integrate.io’s flexibility, ease of use, and competitive pricing make it a highly intriguing option for nearly every ETL use case. Want to learn more about how Integrate.io can help with your ETL needs? Get in touch with our fantastic customer support team today for a chat about your situation and schedule a pilot to try the Integrate.io platform for yourself.