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ETL tool comparison: How to pick the best one? [2023 Guide]

Simplify your ETL tool comparison by following the seven criteria on how to choose the best one for you.

How To
March 21, 2023
ETL tool comparison: How to pick the best one? [2023 Guide]
Simplify your ETL tool comparison by following the seven criteria on how to choose the best one for you.

With so many ETL solutions on the market that help you streamline and automate your extract, transform, and load data pipelines, it’s hard to find the best tool for your organization.

In this article, we'll simplify your ETL tool comparison by highlighting the best tools on the market right now and outlining seven criteria you can use to decide which one to use. Use this free downloadable checklist and evaluate the best tools yourself:

  1. Keboola
  2. Fivetran
  3. Talend Open Studio / Stitch
  4. Matillion
  5. Pentaho
  6. Informatica 
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Set up a user-friendly, transparent, scalable, and license-free ETL process in minutes. Start for free.

The best ETL tools for you & their key features

Make your ETL tool comparison faster and easier by checking the best ETL tools on the market. 

Whether open-source or ETL SaaS app providers, here is an overview of the top contenders based on their main features and who they are best for.

1. Keboola

Keboola is a data platform as a service that helps you automate all your data operations. Its core feature is to build and automate ETL, ELT, and reverse ETL data pipelines.

Key features:

  • Automated pipelines end-to-end. 250+ pre-built connectors help you automate data integration between various data sources (Microsoft Excel, Salesforce, CRMs, REST APIs, etc.) and data storages (Snowflake data warehouse, SQL server, AWS Redshift, Microsoft Azure, Google BigQuery, …).
  • Accessible. ETL processes can be declared via low-code scripting (Python, SQL, R, Julia) or via a no-code, graphical, drag-and-drop user interface. Keboola empowers anyone - whether they are data engineers or domain experts without a single CS class.
  • Powerful transformations. From low-code, CLI, to no-code, unlock the transformation you need to reshape your data.
  • Efficient. Supports efficient data replication via CDC (change data capture).
  • Scalable. The ETL platform is built to scale. Use the dynamic backend for high-performance big data workflows.
  • Extensible. Keboola offers features that cover many data use cases beyond ETL: enterprise data security for every business size, data governance and master data management, DataOps (development branches and versioning, Change Data Capture to speed up replication, CLI), Data Catalog for data sharing, and machine learning toolbox.
  • Users’ #1 choice. Keboola is a crowd-pleaser. But don’t just take our word for it. Check the G2 crowd reviews and awards.
“Instead of separately selecting, acquiring, configuring and integrating an endless list of technologies to build your data stack, Keboola gets you there in one platform.” Robert C., Head of Product at Gymbeam

Best for: Teams of technical data experts (scientists, engineers, analysts) and data-driven business experts who would like an all-in-one ETL solution.
Recommended read: Check how Mall Group used Keboola to automate their ETL pipelines. The result? Their engineering team was able to deliver 400 new data use cases in a single year.

Set up a user-friendly, transparent, scalable, and license-free ETL process in minutes. Start for free.

2. Fivetran

Fivetran is a cloud-based ETL solution primarily focused on the extraction and loading part of the ELT process

Key features:

  • Offers functionality for database and SaaS data replication. Great for embedding customer data processing into your application.
  • Excellent near real-time data replication capabilities. 
  • No native transformation ability. Fivetran relies on dbt Core for transformation, and you’ll have to integrate dbt into your data architecture to transform data. If your main use case is for processing a lot of unstructured data or model data for data analysis, Fivetran might not be the best ETL solution for you.
  • No on-premise solution, only cloud.

Best for: The cloud data engineer who wants to embed common SaaS data into their own application.

Recommended read: Check this detailed comparison of Fivetran and Keboola on 10 different crucial questions

3. Stitch / Talend Open Studio

Talend Open Studio is a product of Talend that also offers paid data integration software, such as Talend Data Fabric as a managed data service for developers, Stitch as a no-code data ingestion tool geared towards analysts, or add-on services like Talend Data Quality and Talend Profiling. But we’ll focus on its popular open-source ETL tool offering.

Key features:

  • Can extract data from various sources. Sources not covered out-of-the-box by Stitch can still be extracted using the company’s extensibility framework.
  • Very intuitive to use.
  • No native transformation abilities. You need to rely on Talend’s data transformation services (sold separately) or find a different solution. 

Best for: The savvy data engineer who likes to tinker with code (solo data member or weekend hobbyist). The ideal user is willing to trade more coding time for a less polished (more high-maintenance) solution that will save money on licensing and usage costs.

4. Matillion

Matillion ETL is a data integration solution that can build ETL data processes through a simple no-code/low-code drag-and-drop user interface (UI). 

Key features:

  • Single data operations scale well with Change Data Capture (CDC) and batch processing ingrained in data operations. 
  • Full support for ETL, ELT, and reverse ETL. The number and types of connectors covered by Matillion are extensive enough to cover the vast majority of use cases.
  • Limited to data warehousing destinations. You can connect your business intelligence/data analytics tool to the data warehouse of your choice, but Matillion will not ingest data directly into your data visualization software.

Best for: Database engineers at startups, who would like to build a data model by integrating their various data sources into their data warehouse or data lake.

5. Pentaho Data Integration (previously, Kettle)

Pentaho Data Integration (PDI) is an open-source data integration tool that focuses on data extraction, data transformation, and data loading capabilities to facilitate data engineering work.

Key features:

  • Strong DBA offerings, including database replication, data migration, supports slowly changing dimensions and schemas in data warehousing, etc.
  • Canned transformations. Pentaho comes with samples that show you how to transform data. The canned transformations are customizable, and PDI offers strong support for complex transformation jobs.
  • Low-code. The tool is geared toward a technical audience but implemented as a clickable (not extensively codable) solution.
  • Missing a lot of business connectors, such as any SaaS apps. It is mostly designed for database-to-database data pipelines.

Best for: Cost-sensitive database administrators who want to streamline their data flow jobs with an open-source tool.

6. Informatica

Informatica offers two similar tools: 

  1. Informatica PowerCenter - an ETL platform for large enterprises.
  2. Informatica Cloud Data Integration (ICDI) - a more affordable Integration Platform as a Service (IPaas).

Both are geared towards the largest enterprises (think Fortune 1000 companies) and are market leaders for high-performance data integration at scale. Informatica works in the same space as Microsoft SSIS, IBM’s Information Server, or Oracle Data Integrator (ODI).

Key features:

  • Designed for high-performance big data workflows. It scales seamlessly to huge data sets and complex data organizations.
  • Highly polished and resilient product.
  • There is an obvious lack of viable data destinations for Informatica. The only cloud data warehouse destination it supports is Amazon Redshift. The only data lake destination it supports is Microsoft Azure SQL Data Lake.

Best for: A team of data engineers at a large enterprise who will invest and specialize in Informatica’s custom platform to reap the fruits of a powerful machine.

ETL tool comparison done right - criteria to choose your ETL tool

With so many good options on your ETL tool comparison shortlist, how do you make your final choice for the best ETL solution?

Use this checklist we prepared to compare your final selection head to head. The checklist covers the following criteria:

  1. Key ETL features. Does the tool cover all the applications, databases, and external APIs you need to integrate? Check the connectors offered by the tool against your data extraction and data loading needs. And if you need data transformations, does the tool offer the transformation capabilities you need to make data available for data analytics or business intelligence?
  2. Ease of use. Can the tool be configured and run in a couple of minutes, or is it fueled by sweat?
  3. Target audience. Who is the tool built for? Some tools are for developers, and you need to check whether you know the tool’s language (Java-based tools need a different skill set than SQL-based tools) and use cases (can you build API workflows via CLI scripting?). Maybe you need a data integration tool that can service business experts with no scripting knowledge. In this case, look for a no-code graphical drag-and-drop user interface.
  4. Pricing and Total Cost of Ownership (TCO). Open-source ETL tools are renowned for their low entry costs. There are no vendor fees, no licensing, and no consumption caps. But you pay the bill down the line with higher maintenance costs and costly data engineering hours to customize the ETL solution to your data integration needs. The opposite is true of vendor ETL app providers. They cost more to start with, but they help your ETL processes up and running from the get-go and take care of maintenance. 
  5. Security. Open-source ETL tools are usually worse than vendor tools at security. From regulation-compliant data processing (GDPR) to lineage tracing, check how your tool keeps your data safe at rest and in transit. If you operate in an especially sensitive area, pick tools that can be run on-premise where you can configure your own complex data security instead of web-based or cloud-based tools.
  6. Support and documentation. When things go wrong, is there a strong support system, such as vendor-guaranteed SLAs for support? Or if the tool is open-source, is there a strong community of users who can answer your questions (e.g. on StackOverFlow)? Is there extensive documentation you can rely on? 
  7. Additional functionalities. From machine learning to data management and automation features that save you time, the “bonus features” can be a decisive input into your tool choice. You come for the ETL process and you stay for all the data processes it helps you automate. 

Recommended reads: Looking for a more focused ETL tool comparison? Check the following guides for:

  1. ETL tools specialized for Snowflake.
  2. Free and open-source ETL tools.
  3. Python ETL tools.

Automate all your data operations with Keboola 

Keboola is hands down the best ETL solution for your organization:

  1. Build out-of-the-box ETL data pipelines in minutes with automation.
  2. Its intuitive and easy-to-use design makes it a crowd favorite.
  3. Adjust Keboola to work with your team - from low-code features for engineers to no-code features for domain experts who don’t know how to code.
  4. Affordable. Start building data flows without breaking the pipeline. With its always free tier, you don’t even have to swipe the credit card to streamline your data processes with Keboola.
  5. Enterprise-grade security that covers all the data regulations.
  6. Extensive support, documentation, and even a Keboola academy to learn advanced ETL features.
  7. Highly extensible. From machine learning to data governance, Keboola is packed with features that streamline and automate all your data operations 

Build your first ETL workflow in minutes without even swiping the credit card.

Try Keboola today.

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