Kind Reader, when you’re working with data, you need the right tools to transform, store, and move data efficiently. Azure Data Factory and Fivetran are two popular services that help you achieve these goals. While both services offer similar capabilities, each has its strengths and weaknesses. In this article, we’ll compare Azure Data Factory vs Fivetran, so you can make an informed decision about which one is right for your data integration needs.
Overview of Azure Data Factory and Fivetran
Managing and integrating data from various sources can be time-consuming and complicated. With tools like Azure Data Factory (ADF) and Fivetran, businesses can automate the process, save time, and enhance data accuracy. Both ADF and Fivetran enables a modern cloud architecture, helps streamline data and implement any data flow. However, they have varying features and capabilities that businesses need to consider before deciding on the best fit.
What is Azure Data Factory?
Azure Data Factory is a cloud-based ETL/ELT data integration service. It enables businesses to move data from various sources to different targets in an automated process. The tool provides extensive transformation and mapping capabilities. Also, it can integrate with other analytics services on the Azure platform such as Azure Synapse Analytics and Azure Databricks for a complete end-to-end analytical solution. One of the distinct characteristics of ADF is that it operates in a serverless environment. This nature enables ADF to handle vast data processing volume and scaling in an economic and agile manner.
What is Fivetran?
Fivetran is a cloud-based data pipeline that simplifies data integration from various sources into a destination warehouse for analysis. Fivetran provides pre-built connectors that enable data pipelining and provides daily updates on data transfers. Fivetran is designed to operate in a minimal configuration environment and is best suited for small and mid-sized businesses looking for a simple and cost-effective data integration solution. Unlike ADF, Fivetran doesn’t offer transformation capabilities, which may not be ideal for complex enterprise setups.
Data Integration and Transformation Capabilities
The primary function of data integration tools is to enable data movement and transformation. In this section, we compare the data integration and transformation capabilities of ADF and Fivetran.
Azure Data Factory Integration and Transformation Capabilities
Azure Data Factory provides comprehensive data integration and transformation tools. It integrates with many Azure and non-Azure data sources, including Hadoop and other databases. You can use ADF to perform data transformation by filtering, joining, aggregating, and sorting data. Additionally, it provides mapping capabilities with visual editors for defining complex and straightforward mappings.
Fivetran Integration and Transformation Capabilities
Fivetran enables straightforward data integration with minimal configuration and coding. The tool provides an easy-to-use interface for non-technical users to map tables from source to target data stores. However, unlike ADF, Fivetran has no transformation capability, and you have to perform that separately using SQL or other ETL Tools.
| No | Azure Data Factory | Fivetran |
|---|---|---|
| 1 | ADF has data transformation capabilities for ETL/ELT | Fivetran has no data transformation capabilities, SQL or other solutions required |
| 2 | ADF provides visual drag and drop interfaces for ETL/ELT operations | Fivetran does not allow custom mapping but has predefined connectors for data Pipelining |
Capability
When it comes to the capability of Azure Data Factory vs Fivetran, both platforms have their strengths and weaknesses. One of the most significant strengths of Azure Data Factory is its ability to work with a wide range of data sources, including third-party sources. This means that users can use Azure Data Factory to integrate data from different sources and move that data to where it’s needed.
Sub-Summary – Azure Data Factory Capability
Azure Data Factory’s capability is its ability to integrate a vast range of data sources and move data to where it’s needed.
Sub-Summary – Fivetran Capability
On the other hand, Fivetran is also a capable platform, but it is designed to work with a narrower range of data sources, and it focuses mainly on extracting data from sources and moving it to a destination; usually, a data warehouse.
| No | Azure Data Factory | Fivetran |
|---|---|---|
| 1 | Can work with a vast range of data sources | Works with a narrower range of data sources |
| 2 | Moves data to where it’s needed | Extracts data from sources and moves it to a destination |
| 3 |
Note: Table above shows the comparison of Azure Data Factory and Fivetran capabilities.
| No | Criteria | Azure Data Factory | Fivetran |
|---|---|---|---|
| 1 | Data source compatibility | Supports a wide range of data sources including on-premise, cloud, and SaaS applications | Limited data source compatibility with predominantly cloud-based sources |
| 2 | Data Transformation | Robust data transformation capabilities with data flows and mapping features | Limited data transformation capabilities with no mapping features |
| 3 | ETL Or ELT | Supports both ETL and ELT data integration approaches | Primarily supports ELT data integration approach |
| 4 | Cost | Includes free data movement up to 5,000 activity runs per month and cost increases with higher usage | Offers flat rate pricing regardless of usage volume with no free option |
| 5 | Deployment | Can be deployed on the cloud or on-premise | Cloud-only deployment option |
| 6 | Supported Data Warehouses | Integrates with various data warehouses including Azure SQL Data Warehouse, Snowflake, and Amazon Redshift | Integrates with a limited number of data warehouses including Google BigQuery, Amazon Redshift, and Snowflake |
Features comparison between Azure Data Factory and Fivetran
When it comes to comparing Azure Data Factory and Fivetran, it’s essential to understand their key features to make informed decisions for your business needs. Both of these tools are designed to streamline the data migration and integration process; here we have compared their features.
Data Integration
Azure Data Factory supports integration with various data sources like Azure SQL Database, Cosmos DB, Oracle, Salesforce, SQL Server, and more. On the other hand, Fivetran offers integration with a wider range of sources that primarily include databases, applications and flat files. It supports sources like Amazon Aurora, Amazon Redshift, Oracle Database, Google Analytics, and other major data sources.
Data Transformation and Mapping
Data transformation and mapping are the processes of cleansing, aggregating and structuring data into targeted formats for easily accessible and meaningful analysis. Both Azure Data Factory and Fivetran offer an array of ETL functions, i.e. Extract, Transform, Load, however, these data transformation functions are a bit primitive in Azure Data Factory compared to Fivetran. Hence, Fivetran is preferred for performing high-end data transformations.
| No | Azure Data Factory | Fivetran |
|---|---|---|
| 1 | Supports integration with various data sources like Azure SQL Database, Cosmos DB, and more. | Offers integration with a wider range of sources that includes databases, applications, and flat files. |
| 2 | Offers primitive ETL functions for data transformation. | Offers high-end ETL functions for complex data transformations. |
Integration with other services
Azure Data Factory and Fivetran are both designed to be integrated with other services, but there are some differences to keep in mind.
Azure Data Factory Integration
Azure Data Factory integrates with the entire range of Azure services, including:
– Azure Storage
– Azure Data Lake Storage
– Azure SQL Database
– Azure Cosmos DB
– Azure HDInsight
– Azure Databricks
– Azure Synapse Analytics
– And many more…
This makes it an ideal choice for organizations that rely heavily on other Azure services. With a single click, you can create an Azure Data Factory instance and start working with your existing Azure services. You can also use Azure Data Factory to integrate with non-Azure services, such as Salesforce, Dropbox, and Google Drive.
Fivetran Integration
Fivetran offers over 150 pre-built connectors that allow you to integrate with a wide range of services, including:
– Salesforce
– Hubspot
– Google Analytics
– Facebook Ads
– And many more…
Additionally, Fivetran offers a REST API that allows you to create custom connectors for services that are not supported out-of-the-box. While Fivetran is not limited to integrating with cloud-based services, it does not offer the same level of integration with Azure services as Azure Data Factory.
Both Azure Data Factory and Fivetran offer a high degree of integration with other services, but Azure Data Factory is a better choice if you rely heavily on other Azure services.
Difference in Pricing
One of the biggest differences when comparing Azure Data Factory vs Fivetran is pricing. Both solutions offer a pay-as-you-go pricing model.
Azure Data Factory Pricing
Azure Data Factory offers three tiers of pricing:
- Consumption: you pay based on your usage of services and resources
- Standard: this pricing is based on the number of activities, pipelines, and data movement
- Premium: this pricing is based on the number of activities, pipelines, and data movement, and is suitable for large organizations with a high volume of data
The consumption tier is the most cost-effective option because you only pay for what you use.
Fivetran Pricing
Fivetran offers a flat-rate pricing model based on the number of connectors you use and the number of rows of data you are transferring each month. This can be a more predictable pricing model.
| No | Fivetran Pricing | Azure Data Factory Pricing |
|---|---|---|
| 1 | Flat-rate pricing based on number of connectors and rows of data transferred | Offers three tiers of pricing based on usage of activities, pipelines, and data movement |
| 2 | More predictable pricing model | Consumption tier is most cost-effective option |
Availability and Pricing
One of the significant considerations in selecting the right ETL tool for your data integration requirements is the cost of the software. In this section, we’ll discuss the pricing models for Azure Data Factory and Fivetran and also examine their availability across multiple regions.
Availability
Azure Data Factory is offered as a platform as a service (PaaS) solution by Microsoft, with data centers located around the world. The software is available in the regions where Microsoft provides massive data centers. The platform is accessible from ten global regions: West US, Central US, East US, North Europe, West Europe, East Asia, Southeast Asia, Brazil South, Japan East, and Australia East.
In contrast, Fivetran has data centers in five regions globally: US East, US West, EU West, Asia Pacific, and Australia. However, Fivetran has more than 150 integrations with other data sources, making it more versatile when sourcing data.
Pricing
Azure Data Factory pricing models are based on a monthly pay-as-you-use basis. The platform does not have initial charges or termination fees. Azure Data Factory has two pricing models: Consumption-based and Enterprise. Consumption-based pricing charges for data-integration activity and data movement with an Azure Data Factory pipeline. On the other hand, the Enterprise pricing model is only applicable for those with at least $50,000 per year with the software and with more than 10 pipelines.
Fivetran’s licensing model and pricing is more straightforward than Azure Data Factory. Fivetran charges a subscription-based pricing model per connector per month. If you need additional data transfer, Fivetran offers increment-based pricing per month instead of punitive measures in case you went over the data transfer amount.
| Tool | Pricing Model |
|---|---|
| Azure Data Factory | Pay as you go or Enterprise Subscription-Based |
| Fivetran | Subscribed-based pricing per connector per month or Increment-based pricing per month |
Note that the pricing for each ETL tool may change without prior notice. Please make sure to check the official vendor’s website before making your purchase decision.
Key Differences Between Azure Data Factory and Fivetran
Although Azure Data Factory and Fivetran share some common similarities, there are some key differences between them as well. Here are some of the differences:
1. Data Integration
One of the key differences between Azure Data Factory and Fivetran is the way they integrate data into your data warehouse. Azure Data Factory is a general-purpose data integration service that can be used to ingest and transform data from various sources. Fivetran, on the other hand, is a dedicated data integration service that automates data pipeline management. It is designed to connect with various data sources and send data to your data warehouse in a structured manner.
2. Workflow Orchestration
Another difference between Azure Data Factory and Fivetran is their approach to workflow orchestration. Azure Data Factory provides a complete workflow management solution that allows you to create, schedule and manage complex data pipelines. It enables you to orchestrate and automate data movement and transformation activities across your on-premises and cloud environments. Fivetran, on the other hand, focuses primarily on data integration and pipeline automation. It does not provide a complete workflow management solution but rather focuses on automating the data pipeline between data sources and your data warehouse.
| No | Azure Data Factory | Fivetran |
|---|---|---|
| 1 | General-purpose data integration service | Dedicated data integration service |
| 2 | Complete workflow management solution | Focuses primarily on data integration and pipeline automation |
Azure Data Factory vs. Fivetran
Choosing the right data integration platform can be challenging. Here’s a list of frequently asked questions to help you evaluate Azure Data Factory and Fivetran.
1. What is Azure Data Factory?
Azure Data Factory is a cloud-based ETL (extract, transform, load) service that handles data integration at scale. It allows you to create, schedule, manage, and monitor data pipelines from a variety of sources, such as on-premises data sources, cloud-based data stores, and SaaS applications.
2. What is Fivetran?
Fivetran is a cloud-based data integration platform that helps you replicate data from a variety of sources and load it into a data warehouse, such as Snowflake, Amazon Redshift, or Google BigQuery. It has pre-built connectors for many popular data sources, such as Salesforce, HubSpot, and GitHub.
3. Can I use Azure Data Factory to load data into a data warehouse?
Yes, Azure Data Factory supports loading data into a variety of destinations, including Azure Synapse Analytics, Azure Blob Storage, and Azure Data Lake Storage. You can also use it to load data into other destinations via custom connectors or REST APIs.
4. Can I use Fivetran to transform data?
No, Fivetran is primarily a data replication engine and does not provide a data transformation engine. However, you can use a data transformation tool, such as dbt or Talend, in conjunction with Fivetran to transform your data before loading it into your data warehouse.
5. Do I need to have a data warehouse to use Azure Data Factory?
No, Azure Data Factory can also load data into other destinations, such as SQL Server, Oracle, and MongoDB. However, it is optimized for loading data into Azure data services, such as Azure Synapse Analytics and Azure SQL Database.
6. How does pricing compare between Azure Data Factory and Fivetran?
Azure Data Factory pricing is based on the number of data integration activities executed and the amount of data processed, while Fivetran pricing is based on the number of connectors and the amount of data processed. Depending on your use case and data volume, one platform may be more cost-effective than the other.
7. Does Azure Data Factory support real-time data integration?
Yes, Azure Data Factory supports near real-time data integration via change data capture (CDC) and event-based triggers. You can have data pipelines triggered by events, such as files being added to a data store or messages being sent to a message queue.
8. Which platform has more pre-built connectors?
Fivetran has more pre-built connectors than Azure Data Factory. Fivetran has over 150 connectors to popular data sources, while Azure Data Factory has around 90 connectors.
9. Can I use Azure Data Factory to do data cleansing and deduplication?
Yes, Azure Data Factory can use mapping data flows to perform data transformations and data cleansing activities, such as data type conversions, column renaming, and data deduplication.
10. Which platform has better scalability?
Both Azure Data Factory and Fivetran are designed for high scalability. Azure Data Factory can scale up to thousands of data pipelines, while Fivetran can handle millions of rows of data per second.
11. Can I use Azure Data Factory for ELT (extract, load, transform) instead of ETL?
Yes, Azure Data Factory can perform ELT by using data flows to transform data after it is loaded into a destination. This approach can be faster and more cost-effective for certain use cases.
12. Can I use Fivetran to load data into a NoSQL database?
No, Fivetran is optimized for loading data into data warehouses and does not support loading data into NoSQL databases. However, you may be able to use a third-party tool or SDK to accomplish this.
13. Can I use Azure Data Factory for file-based data integration?
Yes, Azure Data Factory can handle various file formats, such as CSV, JSON, and Parquet, and supports file-based data integration via its File System and FTP connectors.
14. Which platform has better security features?
Both Azure Data Factory and Fivetran provide robust security features, such as encryption of data in motion and at rest, role-based access control, and compliance certifications. However, Azure Data Factory has more extensive compliance certifications, such as HIPAA and FedRAMP.
15. Can I use Fivetran to load data into multiple destinations?
Yes, Fivetran can load data into multiple data warehouses and even multiple tables within the same data warehouse. It also supports data replication from multiple sources to the same data warehouse.
16. Can I use Azure Data Factory to move data between cloud providers?
Yes, Azure Data Factory has connectors to various cloud providers, such as AWS S3 and Google Cloud Storage, allowing you to move data between cloud providers or from on-premises to the cloud.
17. Does Fivetran support data versioning?
No, Fivetran does not support data versioning out of the box. However, you can use a version control system, such as Git or SVN, to track changes to your data pipeline configurations and SQL transformations.
18. Can I use Azure Data Factory for data replication?
Yes, Azure Data Factory can perform data replication from a variety of sources to a destination, such as a data warehouse or a SQL database. You can also use it for incremental data loads, such as CDC or delta loading.
19. Can I use Fivetran to replicate data from custom data sources?
Yes, Fivetran provides an API connector and a webhooks connector, allowing you to build custom connections to virtually any data source, even if there is no pre-built connector available.
20. Does Azure Data Factory support real-time monitoring?
Yes, Azure Data Factory provides real-time monitoring and alerts for data integration activities, such as pipeline execution, errors, and resource utilization.
21. Which platform provides better data quality control?
Both Azure Data Factory and Fivetran provide tools for data quality control, such as schema validation, data profiling, and data lineage tracking. However, Azure Data Factory has better support for custom data quality activities via its mapping data flows feature.
22. Can I use Fivetran to load data into BI tools?
Yes, Fivetran can load data into popular BI tools, such as Tableau, Looker, and Power BI, via pre-built connectors or APIs. It also supports column-level permissions to ensure data security.
23. Can I use Azure Data Factory to automate data pipelines?
Yes, Azure Data Factory provides scheduling and orchestration features to automate data pipelines, with support for triggers based on time, events, or external APIs.
24. Can I use Fivetran to replicate data from multiple schemas?
Yes, Fivetran can replicate data from multiple schemas within the same database or data source. It can also perform table filtering and column masking to control which data is replicated.
25. Which platform is more user-friendly?
Both Azure Data Factory and Fivetran offer intuitive user interfaces and easy-to-use dashboards for monitoring data integration activities. However, Azure Data Factory may be more familiar to users who are already using other Azure cloud services.
Learn about the differences between Azure Data Factory and Fivetran to determine which data integration tool best fits your needs for modern data analytics.
Until Next Time, Kind Reader
We hope this article has given you a good understanding of the differences between Azure Data Factory and Fivetran. Whether you’re looking for a more customizable solution or a simpler, more automated option, both tools have their unique advantages. Thank you for taking the time to read through our comparison and we hope to see you back here soon for more informative articles. Keep exploring and stay curious!