All ETL tool comparison

Fivetran vs Airflow

Key differences on use cases, connectors & operators, customization, security, and pricing.

Check the comparison spreadsheet
Fivetran
Fivetran
VS
Airflow
Airflow
VS
Fivetran

Data integration automation tools have revolutionized how businesses handle data management, and among the most prominent options are Fivetran and Airflow. However, choosing a data integration tool that meets your organization’s needs is challenging. Making the correct choice can significantly save your team’s resources, time, cost, and effort.

In this article, let us discuss the key features of Fivetran and Airflow and their differences. The discussion will encompass comparisons based on use cases, flexibility, security, cost, and other relevant factors.

Overview of Fivetran

Fivetran is a modern, cloud-based data movement platform specializing in automating data pipelines. Its wide library of pre-built connectors allows you to streamline the process of extracting, transforming, and loading data between many sources and destinations. Fivetran operates in the ELT (Extract, Load, Transform) format to carry out data integration and helps you integrate with other available cloud-based systems. Additionally, it also allows you to perform complex data management tasks like schema mapping, data transformation, and Change Data Capture (CDC) within a few clicks. 

Key features of Fivetran

  • Data movement: Fivetran allows you to efficiently replicate data from over 400+ source connectors to your selected destination. With the help of these connectors, you can access the required data in minutes without writing any codes.
  • Complex Transformation: To handle complex transformations using Fivetran, you can integrate it with the dbt core. The combination of both tools allows you to write complex transformation models within the data warehouse using Python or SQL.
  • Security: Fivetran secures sensitive data such as PII by employing the column blocking and hashing feature. Column blocking helps you to block specific columns required for replication in your destination. However, column hashing lets you secure PII data from applications before transferring it to the target file. These features reduce the risk of exposing sensitive data, and you can have greater control over the data.
  • Data Governance: With the help of Fivetran’s Meta Data API, you can track every aspect of the data’s journey from source to destination. It also allows you to tag the data by assigning a label to a piece of data and sending these tags to the destination.

Overview of Apache Airflow

Airflow is not a data integration tool. It is an open-source workflow management tool that serves the purpose of creating, scheduling, and tracking batch-oriented workflow for data pipelines. These workflows facilitate tasks such as moving data from source to destination, filtering data sets, implementing data manipulation policies, and overseeing database management tasks. Additionally, the user interface of Airflow makes it easy for professionals with all backgrounds to perform data workflow orchestration seamlessly. 

Key Features of Airflow

  • Open-Source Community: The open-source community of Airflow fosters a robust ecosystem of plugins, integrations, and extensions. This ecosystem enables users to connect the tool with various cloud services, databases, and third-party tools.
  • Operators: Airflow has a vast library of operators. These operators are pre-built templates capable of handling various tasks, such as data transfer, orchestration, cloud operations, and executing SQL scripts.
  • Directed Acyclic Graph (DAG): You can craft workflow in Airflow as a DAG, a  conceptual or graphical representation of a series of activities. This feature simplifies monitoring and constructing complex workflows in a structured sequence.
  • Scheduling: Leverage Airflow’s extensive feature to schedule your workflows, determining their timing and frequency. You can create schedules using cron expressions, intervals, or custom triggers tailored to your requirements.

ETL Tools Comparison: Fivetran Vs Airflow

Fivetran and Airflow are two different tools that differ broadly in use case, features, and usability. Here are some of the key differences between the tools:

Features Fivetran Airflow
Focus Data Ingestion, ELT. Workflow management.
Sources More than 300. More than 30 sources with the transfer operators. Sources are tightly coupled with destinations.
Destinations All main warehouses and databases. All major data warehouses, lakes, and databases. Destinations are tightly coupled with sources.
Customizability of connectors Limited through Fivetran’s Cloud functions. Users can edit any pre-built operator and build their own ones.
Database replication Full table and incremental via change data capture. Full table replication. Incremental replication requires coding your own logic in your Airflow DAGs and SQL files to extract only new data.
Integration with data stack Supports dbt transformations. Integrations can be contributed by the community. Integrate deeply with Kubernetes, dbt, Airbyte, and more.
Support SLAs Available N/A
Security certifications HIPAA, GDPR, SOC 2 N/A
Vendor lock-in Annual contracts. Airflow Core and Operators are open-source
Purchase process Free trial available for low-volume data movement or you can also contact sales for custom pricing. Self-service for managed services with Google Cloud Composer and Amazon Managed Workflows for Apache Airflow (MWAA). Sales for Astronomer.io. Open-source edition deployable in minutes.
Pricing Volume-based pricing with MARs (monthly active rows). Pricing for Cloud Composer is based on CPU, storage, and egress cost. Pricing for MWAA is based on storage and compute cost. Astronomer.io’s pricing isn’t public.
API Available through Powered by Fivetran. Available

{{COMPARISON_CTA}}

Fivetran Vs Airflow: Use Cases

Fivetran is an ETL tool designed for integrating data from multiple sources to destinations. The primary use case of the platform is to automate the complex process of data pipeline management so you can analyze and access data efficiently. Some of the common use cases of Fivetran include: 

  • Seamless integration from various sources to destinations using its wide array of pre-built connectors. 
  • Basic data transformation services, including schema standardization, data aggregation, manipulation, filtering, and more.
  • Change data capture services for certain connectors to access the most current information for critical analysis. 

On the other hand, Airflow is specifically used for the orchestration of data pipelines. It works with batch pipelines that are a sequence of a bunch of jobs with clear start and end points. However, not being designed for data integration, the platform allows you to integrate data with other systems by expanding its functionality. Here are some of the common use cases of the platform: 

  • Orchestration and automating of complex data workflows and pipelines.
  • Data migration from source to on-premise or cloud-based destination such as data warehouse, data lake, Snowflake, Redshift, or AWS. 
  • Data integration in ETL/ELT formats.
  • Automated report generation. 

Fivetran Vs Airflow: Connectors & Operators

Fivetran provides over 300+ pre-built connectors for sources and 14 destination options, including databases, SaaS applications, flat files, and data warehouses. These connectors streamline the process of data extraction and loading from the source to the destination. Being a SasS platform, all the connectors are created and managed by Fivetran's engineering staff. However, it also allows you to create custom connectors for data sources or APIs using Fivetran’s cloud functions. Though it offers a flexible setup and configuration of data pipelines, the flexibility options in this platform are constrained when compared to Airflow.

Since Airflow is not designed to be an ETL tool, it doesn’t have pre-built connectors. However, the platform offers more than 100 operators. Operators are the tools that help orchestrate data pipelines built on other platforms. The operators use Python classes to create a uniform interface for interacting with a wide range of databases, APIs, and cloud services. While Airflow requires more manual configuration and setup, it offers control over data workflows. 

Fivetran Vs Airflow: Customization

Fivetran offers a more streamlined approach using its pre-built connectors and cutting-edge user interface. Most of the operations you perform are pre-defined by the platform. This implies little space for customization, which can be limiting in some cases. For instance, even with a wide library of pre-built connectors, there are cases when the specific source or destination is unavailable on Fivetran. Therefore, it is not an ideal choice for customization. However, Fivetran is well-suited if you are looking for a plug-and-play solution. 

Airflow is designed for flexibility and customization. As an open-source platform, it provides total control over its existing operators and features so that you can tweak them according to your specific business requirements. Airflow also provides a framework for creating custom data workflows and transformation processes using Python scripts. Therefore, developers and engineers can write custom code to define transformation and orchestration logic according to their specific needs. This requires a lot of technical expertise. However, it is ideal for flexible data workflow management needs. 

Fivetran Vs Airflow: Security

Fivetran offers fully managed security services to meet the highest industry standards. The security features provided by the platform include access controls, routine assessments, data encryption at rest and transit, data resilience and backup, and network security protocols. Fivetran is also committed to meeting standard compliance regulations by offering compliance certifications like SOC2  and HIPAA to ensure legal confidentiality and data integrity. 

In contrast, Airflow leaves most of the security and compliance responsibilities to its users. It does provide minimal features like access control, encryption, and authentication to implement security measures. However, the configuration of these is your responsibility. So, the level of security for data management tasks in Airflow is directly related to how well you execute the security measures. Therefore, security and compliance in Airflow are very resource-intensive as compared to Fivetran. 

Fivetran Vs Airflow: Cost 

Fivetran, on the other hand, is a subscription-based tool. It uses a pricing model in which you have to pay for only the resources you use. Fivetran pricing is divided into five parts: Free, Starter, Standard, Enterprise, and Business critical. The costs of each pricing module are different, and as you increase the pricing level, it automates most of the management and infrastructure tasks for you. In Fivetran, costs are mainly associated with the amount of data and the number of connectors used. 

Airflow is a free, open-source tool with a large community of active users. Operators, plugins, libraries, documentation, and everything you need are available for use in its open-source ecosystem. However, you are responsible for setting up and maintaining the infrastructure on which it runs, including server instances, storage systems, and more. Therefore, the costs associated with Airbyte come mainly from infrastructure and management. 

Airbyte: An Alternative Solution to Fivetran and Airflow

Image Source

Airbyte is a popular data integration and ETL tool, serving as a robust alternative to Fivetran and Airflow. It has an extensive library of 300+ pre-built connectors that allow you to connect various data sources to destinations. With the help of a range of services provided by Airbyte, such as no-code connectors and orchestration capabilities, you can seamlessly set up and manage data movement operations.

Some of the key features of Airbyte are:

  • Connector Development Kit: With the help of Connector Development Kits (CDKs), you can build customized connectors in Python. This allows you to integrate Airbyte with a wide range of sources, tailoring your specific integration requirements effortlessly. 
  • Change Data Capture: It supports Change Data Capture (CDC) for some connectors to capture and deliver changes with minimized resource consumption.
  • Certifications: Airbyte holds SOC 2, ISO-27001, and GDPR certifications to comply with rules and regulations regarding sensitive data.
  • Security: Airbyte offers robust security measures for data movement, such as strong encryption, role-based access control, audit logs, and secure data transmission.

Conclusion 

In the detailed comparison between Fivetran and Airflow, you have learned the major differences between both tools. Fivetran is an ideal choice for plug-and-play solutions for data integration tasks. However, if you want flexibility and prioritize workflow management, Airflow should be the choice. 

A good alternative to using one tool over another is using both tools. Fivetran can do the data integration, and Airflow can help you manage workflow efficiently. While the combination of Fivetran and Airflow provides a robust solution, an alternative worth considering is the integration of Airbyte into your data architecture. It is a modern and open-source data integration platform that simplifies the process of collecting, preparing, and loading data across systems of your choice.

Want to know the benchmark of data pipeline performance & cost?

Discover the keys to enhancing data pipeline performance while minimizing costs with this benchmark analysis by McKnight Consulting Group.

Get now

Compare Airbyte's pricing to other ELT tools

1 minute cost estimator

Don't trust our word, trust theirs!

"Airbyte is a very promising solution for the single point of data integration. We continuously migrate our connectors from our existing solution to Airbyte as they became available on Airbyte, and look forward to the release of Airbyte Cloud!"
Apostol Tegko
Apostol Tegko
Data Analyst at Fnatic
"Airbyte made it possible to release and fund our microservices independently, shortening the release cycle time from multiple months to only a few days."
Jins Kadwood
Jins Kadwood
CTO at Agridigital​
"With Airbyte, there is one solution, and everything can run on-premises giving us the flexibility to build what we want without worrying about compliance and reliability issues."
Konrad Schlatte
Konrad Schlatte
Data Engineer at PensionBee

What Airbyte users say

“Airbyte saved us two months of engineering time by not having to build our own infrastructure. We can count on the stability and reliability of Airbyte connectors. Plus, with Airbyte it’s simple to build custom pipelines.”
“With Airbyte, we don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
"I used Airbyte's connector builder to write 2 connectors. The experience was amazing, the setup was straightforward, and in almost no time I was able to develop a new connector and get it running.”
“Using Airbyte makes extracting data from various sources super easy! I don't have to spend time maintaining difficult data pipelines. Instead, I can use that time to generate meaningful insights from data.”
"Airbyte does a lot of things really well. We just had to set it up, and it ran from there. Even moving 40GB worth of data works just fine without needing to worry about sizing up.”