The Top 5 ETL Tools in 2022

  • John Morrell
  • June 4, 2021
The Top 5 ETL Tools in 2021

ETL Tools Market Trends

The ETL tools market continues to grow at a strong pace, reaching $8.5 billion in 2019, and is expected to grow at a CAGR of 13.9% to reach $22.3 billion by 2027.  The market is quite mature, with one of the long-time independent suppliers such as Informatica having been founded in 1993.

But as the ETL market moves into 2022, a number of new trends are driving new growth in the market:

  • Cloud – the high popularity of cloud platforms and data warehouses has caused strong growth in the cloud data integration segment of this market.
  • ELT – with the availability of inexpensive compute resources in cloud data warehouses, a new model of data integration has emerged – Extract, Load, and Transform.
  • Speed and simplicity – with data engineering resources already stretched, new tools look to allow less technical staff to create data pipelines with wizard-driven simplicity.

The combination of these factors has created an overall meta-trend in the ETL market – the disintegration and specialization of the tools.  in the data integration stack.  You can continue to buy a complete end-to-end ETL data integration platform such as Informatica and Talend, but often these tools are complex and target highly technical and experienced ETL developers,

In most modern data stacks focused around cloud data warehouses, the ELT data integration model has introduced two different and focused tools:

  • “EL” tools that make it easy to move data from various sources into your cloud data warehouse.  This includes vendors such as Fivetran and Matillion.
  • Data transformation and modeling tools that perform the T in your ELT directly in your cloud data warehouse.  This includes vendors such as Datameer.

Let’s explore the top 5 vendors in the ETL/ELT data integration market.

What Comes with My Cloud?

The three major cloud platforms offer their own ETL tools: AWS Glue, Azure Data Factory, and Google Cloud Data Fusion.  Each is unique, but all three have limited functionality when it comes to data pipeline definition, with poor dataflow designers that often force users to break down and write ETL code.  In addition, many of the cloud platforms have gaps when it comes to enterprise security and governance, and are not suitable for bridging on-premises and cloud data sources.

A recent GigaOm white paper recently outlined many of the functionality gaps in the cloud vendor ETL tools and recommended using third-party tools.

Data Transformation Tool Leaders


Datameer focuses on the T – transformation – in your ELT stack.  Datameer SaaS Data Transformation is the industry’s first collaborative, multi-persona data transformation platform integrated into Snowflake.  The multi-persona UI, with no-code, low-code, and code (SQL) tools, brings together your entire team – data engineers, analytics engineers, analysts, and data scientists – on a single platform to collaboratively transform and model data.  Catalog-like data documentation and knowledge sharing facilitate trust in the data and crowd-sourced data governance.  Direct integration into Snowflake keeps data secure and lowers costs by leveraging Snowflake’s scalable compute and storage.

Datameer provides a highly scalable and flexible environment to transform your data into meaningful analytics.  With Datameer, you can:

  • Allow your non-technical analytics team members to work with your complex data without the need to write code using Datameer’s no-code and low-code data transformation interfaces,
  • Collaborate amongst technical and non-technical team members to build data models and the data transformation flows to fulfill these models, each using their skills and knowledge
  • Fully enrich analytics datasets to add even more flavor to your analysis using the diverse array of graphical formulas and functions,
  • Generate rich documentation and add user-supplied attributes, comments, tags, and more to share searchable knowledge about your data across the entire analytics community,
  • Use the catalog-like documentation features to crowd-source your data governance processes for greater data democratization and data literacy,
  • Maintain full audit trails of how data is transformed and used by the community to further enable your governance and compliance processes,
  • Deploy and execute data transformation models directly in Snowflake to gain the scalability your need over your large volumes of data while keeping compute and storage costs low.

“EL” Data Integration Tool Leaders

Hevo Data

Hevo Data, a No-code Data Pipeline, assists in moving data from 100+ sources to your desired data warehouse/destination and visualizing it in a BI tool. Hevo is fully controlled and entirely automates the process of not only loading data from your selected source but also enriching the data and changing it into an analysis-ready format without the need for you to write a single line of code. Its fault-tolerant architecture ensures that data is handled securely and consistently, with no data loss.

Hevo’s interesting features:

Completely automated: The Hevo platform can be set up in a matter of minutes and requires very little maintenance.

Transformations: Preload transformations are provided by Hevo via Python code. It also enables you to run transformation code for each event in the pipelines that you create. To carry out the transformation, you must edit the properties of the event object passed as a parameter to the transform method. Hevo also has drag-and-drop transformations such as Date and Control Functions, JSON, and Event Manipulation, to mention a few. These can be configured and tested before being used.

Real-Time Data Transfer: Hevo offers real-time data migration so that you always have analysis-ready data.

Complete and Accurate Data Transfer: Hevo’s solid infrastructure enables dependable data transfer with no data loss.

Scalable Infrastructure: Hevo includes built-in integrations for over 100 sources, including Google Analytics, to let you scale your data infrastructure as needed.

24/7 Live Help: The Hevo staff is accessible 24 hours a day, 7 days a week to provide great support to you via chat, email, and support calls.

Schema Management: Hevo automates schema management by detecting the schema of incoming data and mapping it to the destination schema.

Live Monitoring: Hevo allows you to watch the data flow in real-time so you can see where your data is at any given time.


Fivetran is a cloud-based ELT data integration platform that offers a simple, reliable way to replicate and synchronize data into your cloud data warehouse (CDW).  It is a basic, reliable service that lets you set up “connections” between your data sources – primarily SaaS applications, cloud services, and cloud databases – and your cloud data warehouse.  Transformation capabilities require SQL coding or using an add-on open-source package called dbt.


Matillion is one of the younger, cloud-based ETL solutions on the market. It consists of three components: the underlying platform, a graphical data orchestration tool, and a management tool. Matillion does not have a storage and execution engine, and all data processed in a data flow is stored in its intermediate form in your cloud data warehouse tables.

End-to-End Data Integration Tool Leaders


Informatica offers an end-to-end data integration platform that has an extensive set of capabilities.  The company has a portfolio of data integration and cloud data integration products and areas related to data integration, such as data engineering, data cataloging, data quality, data governance, and master data management.

Informatica’s legacy data integration product – PowerCenter – was designed and optimized for on-premises deployments.  Only recently (in 2018) did Informatica move their data integration products to the cloud in both their own – Informatica Cloud – and on public clouds (AWS, Azure, and GCP).  The main data integration products work with the ETL data flow style model. Many of Informatica’s enterprise features listed above are only available as add-ons or separate products.


Talend offers a comprehensive integration platform covering a full range of integration scenarios.  Talend roots are in an open-source data integration platform.  On the data integration side, they offer a core data integration platform (on-premises or in the cloud), a specialized data replication product for the cloud – Stitch – and related products for data cataloging, data preparation, and data stewardship.

What’s Next

For many, building a modern data stack around their cloud data warehouse is the highest priority for their data and analytics teams.  A modern data stack will deliver the speed and agility they require while also helping to reduce their rapidly escalating data engineering costs.

For you, the next steps are to evaluate two types of tools: “EL” tools for moving your data into the cloud data warehouse, and data transformation and modeling tools for transforming data directly in your cloud data warehouse to put it in final analytics form.

Are you interested in learning more about Datameer and how it can deliver agility and collaboration for the “T” in your modern ELT data stack?  Please visit our website or Sign up for your free trial today!



Related Posts