What Are the Top ETL Tools for Azure Data Warehouse?

Azure Synapse Analytics, still commonly known as Azure Data Warehouse, is Microsoft's cloud data warehouse that processes relational and non-relational data for analytics. As one of the most popular data warehousing tools, Azure lets you generate real-time insights into almost every aspect of your business, from sales to customer service. But how do you get data to Azure in the first place? That's where an Extract, Transform, and Load (ETL) tool proves useful.

It's a platform that extracts data from sources like Salesforce, relational databases, customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, and more. Then it transforms that data into the correct format for analytics and loads it to the Azure data warehouse. There's little (or no) code involved so you can save money on data engineers. There are several ETL tools for Azure Data Warehouse available on the market. All of these platforms do the same thing: They move your data to Azure so you can run that data through business intelligence (BI) tools for deep data insights. 

But which of these tools provides the biggest bang for your buck? Here are the best ETL tools for Azure Data Warehouse based on price, features, capabilities, and other factors.

Integrate.io 

Integrate.io is one of the most reliable ETL solutions for efficient data processing in Azure Data Warehouse. It comes with over 200 out-of-the-box connectors that sync data to warehouses like Azure, as well as data lakes and other destinations. Integrate.io takes care of the entire ETL process for your team, so there's no need to build data pipelines or hire expensive data engineers. Here's how it works:

1. Integrate.io extracts data from your relational database, CRM, ERP, or another system. There's no code required.
2. It transforms the data into the correct format for third-party BI tools, removes data inconsistencies, and improves data quality.
3. It loads data to Azure so you can run it through BI tools for analytical purposes.

Other Integrate.io features include:

• A REST API.
• Top-tier customer service, including telephone and email support.
• Online guides and tutorials.
• A Salesforce-to-Salesforce connector that moves Salesforce data to Azure and then back again.
• Streamlined workflows.
• A simple drag-and-drop interface.
• Connectors for other data warehouses like Snowflake and Redshift.
• A user score of 4.3/5 on the software website G2.com, making it one of the highest-rated ETL tools for Azure Data Warehouse.

G2 Rating: 4.3 / 5, making it a highly-rated ETL tool for Azure Data Warehouse environments

Pros:

• Fixed pricing with unlimited usage tiers

• Easy to use for both analysts and engineers

• Strong compliance (SOC 2, GDPR, HIPAA)

• Excellent onboarding and support reputation

Cons:

• Less customization for complex code-heavy pipelines

• UI performance may degrade with large workflows

• Some connectors may lag behind competitors in update frequency

Pricing:

• Integrate.io pricing is fixed fee, unlimited usage based.

Here's what some users say about Integrate.io:

• "Clear UI, easy to use, and implement. The number of ETL functionalities is very impressive."
• "Intuitive interface, a wide range of data source connections, powerful data manipulation tools, and excellent customer support eager to help."
• "Most of Integrate.io's customer success engineers are amazing."

Fivetran

If you're searching for ETL tools for Azure Data Warehouse, Fivetran might provide a solution. It migrates data from its source to Microsoft's cloud data warehouse in mere minutes so you can push that data through BI software and generate real-time data reports. However, Fivetran reverses the 'transform' and 'load' stages of the ETL process, meaning it doesn't change data to the correct format for analytics until it loads that data to Azure. This process is called Extract, Load, Transform, or ELT. ELT might suit organizations that don't need to process large amounts of data.

Those that do will soon learn that Fivetran struggles with bigger data loads, making alternative ETL tools for Azure Data Warehouse a better option in some use cases. Still, Fivetran has lots of features that make it a worthwhile investment, including excellent customer service and a good selection of native no-code connectors. Unlike Integrate.io, the platform uses a volume-based pricing model that charges customers for the amount of data consumed.

G2 Rating: 4.2 / 5 
Features:

• Fully managed ELT with 700+ prebuilt connectors

• Automatic schema drift handling

• Change Data Capture (CDC) support

• Native integrations with Snowflake, BigQuery, Redshift, Databricks

• Role-based access control and logging

Pros:

• Minimal maintenance and automated pipeline reliability

• Highly scalable for large enterprise data volumes

• Robust schema evolution support

• Extensive documentation and support

Cons:

• Usage-based pricing (active rows) can escalate quickly

• Requires dbt or external tools for transformation logic

• Limited flexibility for custom workflows or scripting

Pricing:

• Volume-based pricing (based on active rows)

• Free trial available

• Exact pricing varies by usage and connector type

Read more: Fivetran vs. Integrate.io

Stitch

Stitch handles large data loads like Integrate.io (its primary data transfer method is ETL, not ELT). However, it has limited transformation abilities, focusing on 'extract' and 'load.' This method might suit companies with data that doesn't require lots of transformation. For example, Salesforce data, but it restricts users that want to convert legacy data into a usable format for analytics. On the flip side, Stitch comes with over 100 native connectors that make pipeline-building easy, as well as a reliable customer service team. You can also scale Stitch as your data requirements grow. 

G2 Rating: 4.5 / 5
Features:

• ELT platform with ~140 connectors

• Supports batch and incremental data replication

• Basic scheduling and logging

• Integrates with Singer open-source framework for custom connectors

Pros:

• Fast setup and minimal learning curve

• Affordable for small teams

• Transparent pricing

• Open-source extension (Singer taps)

Cons:

• No built-in transformation capabilities

• Fewer connectors and features compared to Fivetran

• Slow product development post-acquisition

Pricing:

• Standard: ~$100/month (up to 5M rows)

• Advanced: ~$1,250/year

• Premium: ~$2,500/year

Learn more: Stitch vs. Integrate.io

Matillion

Like Fivetran, Matillion reverses the 'T' and 'L' components of ETL and transforms data into the correct format for analytics after loading it to Azure. Again, this method might suit smaller teams. Another thing to consider is that Matillion uses Azure for processing power. Unlike Integrate.io, this platform doesn't have a data engine. The positive: Matillion comes with an excellent selection of connectors that sync various sources and destinations on top of Azure. You can also code custom scripts in Python and SQL for even more advanced data pipelines.

G2 Rating: 4.4 / 5
Features:

• ELT and orchestration tool purpose-built for cloud data warehouses

• Visual job builder with Python & SQL support

• Native integration with Snowflake, Redshift, BigQuery, Databricks

• Job scheduling, versioning, and pipeline parameterization

Pros:

• Deep transformation capabilities with rich component library

• Built for modern cloud-native environments

• Python extensibility and logic handling

• Scales with enterprise-grade deployments

Cons:

• Credit-based pricing can be complex and costly at scale

• Limited number of connectors compared to Fivetran

• UI may lag with very complex DAGs

Pricing:

• Starts at ~$2/credit

• Available through AWS, Azure, and GCP marketplaces

• Pricing depends on compute usage and job complexity

Learn more: Matillion vs. Integrate.io

Azure Data Factory

Azure Data Factory is Microsoft's ETL service that syncs data from various sources to Azure Data Warehouse. While this method is quick and easy, it comes with limitations. Data Factory essentially only offers native connectors for Microsoft services, so you won't be able to migrate data to other warehouses, lakes, or data stores. There's some support for third-party systems like Redshift, but the number of available connectors is far fewer than all the other ETL tools on this list. 

G2 Rating: 4.6 / 5
Features:

• Cloud-native ETL and data orchestration service

• 200+ connectors including Azure-native and third-party systems

• Code-free data transformation (mapping data flows)

• Supports hybrid data integration with on-premise runtimes

• Built-in scheduling, triggers, and monitoring

Pros:

• Tight integration with Azure ecosystem (Data Lake, Synapse, Databricks)

• Scalable for large data environments

• Support for both no-code and code-driven workflows

• Flexible architecture and pricing

Cons:

• Steeper learning curve for new users

• Pricing can be difficult to predict without usage tracking

• Limited multi-cloud support outside Azure

Pricing:

• Orchestration: ~$1/1,000 activities

• Mapping Data Flows: ~$2/hour (per vCore)

• Total cost depends on data volume, compute used, and frequency of runs

Read more: Understanding Microsoft ETL with Azure Data Factory

Comparison of Top ETL Tools for Azure Data Warehouse

How Integrate.io Can Help You When Comparing ETL Tools for Azure Data Warehouse

All the ETL tools listed above successfully move data to Azure for analytics, so the platform you should choose depends on your requirements. If you have smaller data loads, you might benefit from a tool that transforms data after it loads it to Azure, like Fivetran or Matillion. However, these platforms might prove useless when you scale your business or if your data requirements change. You could use Microsoft's ETL tool, Azure Data Factory. However, this platform primarily benefits Microsoft users, and it's difficult to build pipelines for other warehouses or systems.

Integrate.io is the best choice for Azure data migration because it has ETL and ELT capabilities and syncs with over 100 sources and destinations. You can benefit from world-class customer service, a simple pricing model, a drag-and-drop interface, and more. Want to move data to Azure? Schedule a 7-day demo with Integrate.io and learn more about one of the best tools for Azure Data Warehouse.

FAQs

What are the top ETL tools with Change Data Capture (CDC) capabilities for Azure Data Warehouse (Synapse)?

• Integrate.io provides low-code CDC support with secure data syncing, visual pipeline design, scheduling, and real-time monitoring for Azure Synapse.

• Qlik Replicate offers enterprise-grade CDC replication with transformation, encryption, and audit logging.

• Striim enables real-time CDC pipelines with embedded transformation and validation for low-latency data movement.

• Debezium is an open-source, Kafka-based CDC tool that captures changes from SQL Server, MySQL, or Postgres and streams them into Azure environments.

• Azure Data Factory (ADF) includes native CDC features for Synapse, supporting delta loads with guided configuration.

Which ETL platforms excel at managing real-time data updates for Azure Data Warehouse?

• Integrate.io supports near real-time ingestion and CDC pipeline orchestration into Synapse using a drag-and-drop interface.

• Striim provides high-throughput real-time pipelines with built-in transformation layers and low-latency streaming.

• Qlik Replicate ensures consistent, real-time replication of operational data into Azure with full CDC support.

Why do I need an external ETL tool if I’m using Azure Synapse Analytics?

While Azure Synapse supports built-in data integration, external ETL tools offer:

• Pre-built connectors to hundreds of third-party SaaS apps and databases.

• Advanced transformation layers (UI-based or code-driven) not available natively.

• Cross-cloud orchestration across AWS, GCP, and on-prem systems.

• Enhanced automation, scheduling, and error handling.

• Low-code tools accelerate pipeline development for non-engineers.

Tools like Integrate.io, Fivetran, or Matillion enable full data flow orchestration without being locked into Azure-native tools like ADF.

What features should I look for in ETL tools for Azure Synapse?

Key features include:

• Direct support for Synapse or Azure SQL DWH

• Push-down ELT support (transforms run inside Synapse for scale)

• Incremental loading and CDC support

• Azure AD integration and RBAC

• Blob Storage or ADLS integration (for staging)

Platforms like Matillion and Fivetran push transformations directly into Synapse using SQL, while Integrate.io handles both transformation and orchestration across environments.