Fivetran vs ADF: Key Differences, Features and Use Cases Compared

Fivetran and Azure Data Factory, also known as ADF, are two popular names when it comes to data integration. Both powerful platforms are used for moving data sources to your warehouse or cloud storage. However, the difference between Fivetran vs ADF is in their features, ease of use, and flexibility. We will do a detailed comparison of Fivetran and ADF in this blog.

I will compare their strengths and weaknesses to help you select the best tool suited to your data integration needs. Whether you prioritize automation, scalability, or customization, understanding these platforms will guide you toward the best choice.

Introduction to Fivetran 

Fivetran is an automated data integration tool that makes it easier to sync data from multiple sources into a central data warehouse. Fivetran presents an expansive, pre-built library of connectors for databases, applications, and cloud services that allow businesses to move data between sources easily without the need for complex setup or ongoing maintenance. With Fivetran, organizations can focus on analyzing data instead of managing data pipelines.

Introduction to Azure Data Factory (ADF)

Azure Data Factory (ADF) is a fully managed, serverless data integration service that enables you to collect, transform and move data from several sources. There are more than 90 built-in connectors available to enable easier collection of data from multiple platforms. It is accessible to non-technical users because the no-code interface with ADF makes it accessible for non-technical users to design and manage data workflows without writing a single line of code. ADF also supports Git and CI/CD for building and automating ETL/ELT pipelines, but is accompanied by monitoring features to track your data processes.

Key Differences between Fivetran vs ADF (Azure Data Factory) in One Place

Feature	Fivetran	Azure Data Factory	Hevo
Rating	G2 rating: 4.2/5	G2 rating: 4.6/5	G2 rating: 4.3/5
Business Aspects	Focuses on Data Ingestion and ELT	Supports ETL, ELT, Reverse ETL, and streaming	Supports ETL, ELT, and streaming
Architecture	Supports SaaS, Hybrid, and Self-Hosted deployment models	Cloud-native, fully managed, and supports hybrid solutions	Public SaaS offering hosted on Amazon AWS
Pricing	Usage-based, based on volume of data processed	Based on pipeline orchestration and execution,data flow execution and debugging, and number of data factory operations	Transparent, event-based pricing on the website.
Connectors	500+ Connectors	90+ Connectors	150+ Connectors
Destinations	Databases, Data Lakes, Data Warehouses	Data Sources	Databases, Data Lakes, Data Warehouses
Transformations	Pre-built data models, transformation with dbt integration.	Includes mapping data flows (code-free), Power Query for data wrangling, external transformation using Databricks, and also custom activities.	Supports easy drag-and-drop transformations as well as Custom Transformations using Python
Monitoring	Event Logs from connectors, user actions, API calls; tracks usage, auditing, and troubleshooting.	Provides detailed monitoring of pipeline runs, failure analysis, and custom alerting. Logs are connected to Azure Monitor for proactive monitoring and troubleshooting.	Real-time monitoring, error alerts, activity logs using CloudWatch; monitoring for usage and error tracking
Security	Fivetran uses encryption and compliance with SOC 2, GDPR, and HIPAA. Secure access controls.	Uses Azure Active Directory, encryption at rest and in transit. Also, it follows the key standards (e.g., SOC 1, SOC 2, HIPAA) and more. It provides role-based access control (RBAC).	Data encryption, SOC 2 and GDPR compliance, granular role-based access control
REST API	End-to-end REST API for the management of connectors, monitoring, and API usage.	REST API lets you move data, execute pipelines, and manage resources via Azure Data Factory’s control plane.	Fully functional REST API for managing connectors, pipelines, and error monitoring
Support	Varies by pricing plan	Provides comprehensive support via Azure support plans	Live chat with actual data engineers and not bots

Rating 

• Fivetran: Holds a 4.2/5 rating based on 392 reviews, with 55.9% of reviews from mid-market users,  therefore suitable for smaller to mid-sized companies.
• ADF: Rated 4.6/5 from 80 reviews, with 62.7% feedback from enterprise users, which shows wide adoption in larger organizations.

Architecture 

Fivetran Architecture 

Fivetran offers three architecture deployment models:

• SaaS Deployment: Totally managed in Fivetran’s cloud, so you get a totally hands-off approach.
• Hybrid Deployment: Local data processing with cloud orchestration for compliance and security needs.
• Self-Hosted Deployment: Run Fivetran on private servers and keep full control of data integration.

To learn more about Fivetran architecture, visit the Fivetran architecture.

ADF Architecture

ADF is a cloud-based data integration service that orchestrates data movement and transformation. 

ADF offers a cloud-based deployment model, managed entirely by Microsoft Azure.

Pricing

Fivetran Pricing

Fivetran uses a usage-based pricing model. You pay for Monthly Active Rows (MAR), which are unique identifiers tracked each month. The prices offer the following plans:

• Free: Up to 500,000 MAR for low-volume use.
• Starter: Basic SaaS, events, and file connectors for small teams.
• Standard: Most popular plan for database sources.
• Enterprise: High-volume and real-time data syncing.
• Business Critical: Advanced security for industries like healthcare.
• Private Deployment: For secure, standalone solutions.

More details can be accessed from Fivetran Pricing.

ADF Pricing

Azure Data Factory (ADF) pricing is calculated on consumption basis and includes the following elements:

• Pipeline Orchestration: It is charged based on pipeline execution.
• Data Movement: Pricing for cross-region or storage data transfer.
• Data Flow: Pricing for data transformation.
• Activity Runs: Pricing for every activity in pipelines.
• Integration Runtimes: Usage-based

Pricing varies by region, services, and consumption. Check more details on the Azure Pricing page.

Integrations 

Fivetran Connectors & Destinations

Fivetran seamlessly integrates with a vast array of sources and destinations to make data movement smooth. The total number of over 500+ connectors supported can be used for applications, databases, event tracking systems, and many more. Among the connectors provided include popular platforms like Salesforce, Google Analytics, and MySQL. As for destinations, databases, data warehouses, and data lakes are supported by Fivetran; hence, versatility to cater to wide-ranging data needs is established. This ensures a seamless flow of data from its source to the preferred destinations with minimal setup.

For more details, refer to Fivetran Connectors & Fivetran Destinations. 

ADF Connectors & Destinations

Azure Data Factory supports hundreds of data stores and formats through various activities such as Copy, Data Flow, Lookup, etc. You can connect popular cloud services, databases, file systems, and NoSQL data stores like Azure Blob, SQL Database, Amazon S3, and Google BigQuery using ADF. It also supports interoperability with SaaS applications, where there are connectors for Salesforce, Google Sheets, and Dynamics 365. The platform supports a number of file formats, including Parquet, JSON, and Avro.

For further information, refer to Azure Data Factory connector overview.

Transformations

Fivetran Transformations

Fivetran provides two main transformation solutions:

1. Pre-built Data Models: These models transform raw data into analytics-ready datasets, with no-code setup and automated schedules.
2. Integration with dbt Core, dbt Cloud, and Coalesce: Centralizes and maintains all transformations, with features including version control, testing, and documentation.

ADF Transformations

Azure Data Factory offers you multiple options to transform data inside your pipelines. 

• You can use mapping data flows for no-code, graphical data transformations. Data wrangling enables you to prepare data without writing code using Power Query. 
• For more complex needs, you can use external compute environments like HDInsight, Databricks, or custom activities to execute advanced transformations, like Spark, Python, or custom logic. 
• You can also use machine learning services for predictive analytics and call stored procedures for data manipulation​.

Security 

Fivetran Security

Fivetran protects customer data in all of its integrations. It has the following deployment models: SaaS, Hybrid, and Self-hosted (HVR). Fivetran relies on strong encryption: SSL/TLS for data transfer. It makes use of multi-factor authentication and complies with industry standards such as SOC 1/2, PCI-DSS, and ISO 27001. Connections are monitored, and access is limited to strictly necessary personnel. Customers have the functionality of controlling access permissions and using Single Sign-On (SSO) for safe authentication.

For full security policies, consult their Security Documentation.

ADF Security

Azure Data Factory adopts secure data transfer by following the endpoints of encryption, authentication, and even compliance standards such as GDPR. Transfer your data with SSL/TLS; this means your connection is secure, and users might have different access control permissions. Network security features and private endpoints enable control over the flow of data, ensuring that unintended and unauthorized people cannot have access.

To learn more, check out Azure’s Data Movement Security Considerations.

Ideal Use Cases for Fivetran and ADF

Fivetran

1. Automated Data Integration: It automatically loads data from SaaS apps as well as databases making extraction less painful.
2. Real-Time Analytics: Data is kept in sync for up-to-date reporting and dashboards.
3. Schema Management: It auto-adjusts in case of schema changes, so making it suitable for non-technical teams.
4. Centralized Data Pipelines:  Really fits organizations which need management of connectors from different sources

This makes Fivetran a great fit for businesses focused on analytics-ready data with minimal maintenance.

ADF

1. Data Migration and Integration:  Migration of large datasets across Azure and on-premises environments.
2. ETL and ELT Workflows: Handling complex data transformation and enrichment prior to analytics.
3. Big Data Processing: Integration with Azure Synapse and Databricks for processing and analysis.
4. Data Orchestration: Managing data flow and processing across multiple sources and services.

This makes ADF well-suited for organizations that rely on the Azure ecosystem.

How does Hevo Compare with Fivetran and Azure Data Factory?

Here’s a quick look at where Hevo shines compared to Fivetran and Azure Data Factory:

• Quick and Easy Setup: Unlike ADF’s complex configuration and Fivetran’s dependency on technical adjustments, Hevo’s no-code, user-friendly interface makes it faster and easier to set up and manage data pipelines.
• More Reliable Real-Time Sync: Hevo’s near real-time data sync is robust and ensures that data flows continuously, giving it an edge in situations where up-to-date data is critical for decision-making.
• Built-in Transformation Capabilities: Hevo enables flexible in-pipeline transformations, handling data formatting and processing without needing external tools, which is more seamless compared to ADF’s external transformation reliance.
• Round-the-Clock Support for Fast Issue Resolution: Hevo provides 24/5 support with actual data engineers, helping to quickly resolve issues and minimizing downtime, whereas support from Fivetran or ADF can vary by pricing plan or Azure support levels.

Take a look at the differences between Hevo and Fivetran in detail.

Final Thoughts

Overall, Fivetran and ADF serve different needs: Fivetran would be good for organizations that need to set up quickly and have data move automatically, ideal for analytics-focused use cases with minimal overhead. ADF is best suited for Azure users who require deeper ETL workflows that can be integrated with the Azure ecosystem. It simply depends on the kind of ecosystem you are using and just how much data you require.

If a no-code, user-friendly solution with a wide range of integrations is what you are looking for, do try Hevo.

Sign up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Frequently Asked Questions