Startup Strategy

Top 11 ETL Tools in 2025

CloudVital Team

June 10, 2025

8 min read

ETL (Extract, Transform, Load) remains a foundational process for modern data operations, enabling organizations to move and prepare data across systems, clouds, and analytics platforms. But with the shift toward cloud-native infrastructure, streaming data, and AI-enhanced automation, the ETL landscape in 2025 is more diverse than ever.

Here are the top 11 ETL tools widely used in 2025, ranging from classic enterprise solutions to modern, cloud-native and real-time platforms.

Informatica PowerCenter / IDMC

A long-time enterprise favorite, Informatica continues to lead in complex data integration and governance. Its newer cloud-native offering (Intelligent Data Management Cloud) supports hybrid and multi-cloud environments, ideal for large enterprises managing sensitive or regulated data.

Best for: Enterprise data governance, MDM, large-scale legacy modernization

Microsoft SQL Server Integration Services (SSIS)

Still widely used, SSIS is a staple for teams operating within the Microsoft ecosystem. Though not cloud-native by default, it integrates well with Azure Data Factory for lift-and-shift scenarios.

Best for: SQL Server-based on-premise systems or hybrid Azure environments.

IBM InfoSphere DataStage

A robust platform for high-volume ETL workloads, IBM DataStage is still used heavily in financial services and regulated industries. Its integration with IBM Cloud Pak for Data brings it into the modern containerized era.

Best for: Legacy-heavy enterprises with complex ETL logic and governance requirements.

Oracle Data Integrator (ODI)

ODI is designed to handle large-scale, performance-driven ELT (Extract, Load, Transform) processes in Oracle-heavy environments. Its declarative design and automation are still relevant in 2025 for businesses already deep in the Oracle stack.

Best for: Oracle environments looking to optimize performance and reuse existing data infrastructure.

SAP Data Services

SAP’s enterprise ETL platform works closely with SAP HANA and other enterprise data warehousing systems. It supports both batch and real-time data integration; useful for customers in logistics, finance, and manufacturing.

Best for: Organizations using SAP ERP or SAP HANA with enterprise data workflows.

AWS Glue

A fully managed ETL service on AWS, Glue supports both visual and code-based workflows using PySpark and Python. Its deep integration with other AWS services and ability to scale on demand make it popular for cloud-first teams.

Best for: Serverless ETL in AWS environments, especially with S3, Redshift, and Athena.

Azure Data Factory

Microsoft’s ADF offers data orchestration, pipeline scheduling, and hybrid data movement capabilities. With drag-and-drop UI and custom logic blocks, it suits teams migrating to or operating in Azure Synapse and other MS cloud services.

Best for: Cloud-native or hybrid Azure data workflows, especially when integrating with SSIS.

Google Cloud Data Fusion

Based on the open-source CDAP platform, Data Fusion is GCP’s fully managed ETL/ELT tool. It offers both visual and code-based interfaces and integrates tightly with BigQuery, Dataflow, and Cloud Storage.

Best for: GCP-centric teams seeking fast, scalable, no-code/low-code pipeline building

DBT (Data Build Tool)

Though technically not an ETL tool in the traditional sense, dbt owns the "T" in ELT and is essential in modern cloud warehouses. It enables modular, version-controlled SQL transformations and integrates with Git, CI/CD, and testing tools.

Best for: Teams using BigQuery, Snowflake, Redshift, or Databricks and prioritizing analytics engineering.

Apache Airflow

A widely adopted open-source orchestration tool, Airflow is used to schedule and manage ETL jobs via Python. It's highly customizable and ideal for teams that need flexible, code-first workflow control across modern data stacks.

Best for: Engineering-heavy teams with diverse sources and custom data workflows.

Estuary

Estuary is gaining ground in 2025 as a real-time ETL platform that bridges the gap between batch and streaming. Built on open-source Materialize and using Flow, it enables users to move data from sources like Kafka, MySQL, and SaaS tools into warehouses in real time, with consistency and schema management built in.

Best for: Teams looking for low-latency, event-driven pipelines that sync data continuously, without managing infrastructure.

So... what do you think of this list?

We’ve included a mix of traditional enterprise tools, cloud-native platforms, and emerging real-time solutions, but every data team is different.

Are we missing your go-to ETL tool? Do you love or hate one of the tools listed? Let us know!

Choosing the right ETL tool in 2025

There’s no single “best” ETL tool. Only the best fit for your stack, your workflows, and your team’s expertise. Some platforms shine in enterprise-scale governance; others excel in lean, fast-moving data teams.

That’s why the right tool still depends on your team and tech stack.

Need support building or modernizing your ETL workflows?

At CloudVital, we provide specialized ETL and data engineering talent, experienced in tools like AWS Glue, Airflow, dbt, Azure Data Factory, and more.

Whether you're augmenting your team short-term or building for scale, our engineers are ready to step in.

Click here to learn more

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