Best ELT Tools for Cloud Data Warehouses

As cloud data warehouses like Snowflake, BigQuery, and Redshift become central to modern data platforms, the need for efficient, scalable ELT (Extract, Load, Transform) tools is greater than ever. ELT allows raw data to be loaded into a warehouse first, and then transformed inside the warehouse using its computing power.

Unlike traditional ETL tools, modern ELT tools are built with cloud-native architecture, parallel processing, and support for large-scale data operations.

Here are some of the best ELT tools used by data engineers and analysts for cloud-based pipelines.

1. dbt (data build tool)

Best for: SQL-based transformations in the warehouse

dbt has quickly become the standard for data transformation in the ELT model. It allows you to write transformation logic in SQL and manage it like application code with version control, testing, and modular design.

Key features:

• Native integration with Snowflake, BigQuery, Redshift, and Databricks

• CI/CD support

• Data testing and documentation

• Open-source and cloud versions available

2. Fivetran

Best for: Fully managed, plug-and-play ELT pipelines

Fivetran handles the extract and load steps by offering connectors to 300+ data sources. It automates schema changes, incremental updates, and error recovery—ideal for teams that want quick setup with minimal maintenance.

Key features:

• No-code configuration

• Automatic schema mapping

• Built-in monitoring and alerts

• Supports major cloud warehouses

3. Airbyte

Best for: Open-source, customizable ELT pipelines

Airbyte is an open-source alternative to Fivetran. It supports a wide range of connectors and allows you to build your own. It’s ideal for teams who need flexibility or want to self-host their pipelines.

Key features:

• 350+ connectors (open and community-built)

• Custom connector development

• Self-hosted and cloud options

• Integration with dbt for transformation

4. Matillion

Best for: Enterprise-grade data integration with a visual UI

Matillion is designed specifically for cloud data warehouses and supports ELT with a drag-and-drop interface. It’s well-suited for large teams and enterprises needing advanced orchestration and security features.

Key features:

• Integration with Snowflake, Redshift, and BigQuery

• Job scheduling and orchestration

• Metadata management and audit logging

• Strong enterprise support

5. Hevo Data

Best for: Real-time data sync and quick deployment

Hevo focuses on real-time ELT with fast setup, reliable data syncing, and a user-friendly interface. It’s a good choice for startups and teams without dedicated data engineers.

Key features:

• Real-time data pipelines

• 150+ data source connectors

• Minimal setup

• Built-in transformation layer

Choosing the right ELT tool depends on your team’s size, technical preferences, budget, and warehouse environment. Tools like dbt and Fivetran are dominant in the modern data stack, while Airbyte offers open-source flexibility and Matillion provides visual power for enterprise users.

Before selecting, consider your data volume, compliance needs, and whether you want control (open source) or simplicity (managed service).