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# AWS Data Pipeline vs Azure Data Factory Comparison - What are their main differences?

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AWS Data PipelineAzure Data Factory[+ Add Product](#)

Reviews

**AWS Data Pipeline** [

4.1/5(24)

](https://www.g2.com/products/aws-data-pipeline/reviews#reviews)

**Azure Data Factory** [

4.6/5(102)

](https://www.g2.com/products/azure-data-factory/reviews#reviews)

Pricing

**AWS Data Pipeline**
No pricing available

**Azure Data Factory**
No pricing available

**Pricing Insights**
from reviews

Time to Implement

**AWS Data Pipeline**
Not enough reviews yet

**Azure Data Factory**
3 months

Based on 7 responses

Return on Investment

**AWS Data Pipeline**
Not enough reviews yet

**Azure Data Factory**
Not enough reviews yet

Perceived Cost

**AWS Data Pipeline**
$$$$$

**Azure Data Factory**
$$$$$

Average Discount

**AWS Data Pipeline**
Not enough reviews yet

**Azure Data Factory**
Not enough reviews yet

Pros & Cons

**AWS Data Pipeline**
Not enough data

**Azure Data Factory**
[
Data Integration (7)
](https://www.g2.com/products/azure-data-factory/reviews?filters%5Bsentiment_snippet%5D=1776955&qs=pros-and-cons#reviews)[
Ease of Use (7)
](https://www.g2.com/products/azure-data-factory/reviews?filters%5Bsentiment_snippet%5D=1777089&qs=pros-and-cons#reviews)[
Debugging Difficulty (5)
](https://www.g2.com/products/azure-data-factory/reviews?filters%5Bsentiment_snippet%5D=1777503&qs=pros-and-cons#reviews)[
Difficult Debugging (4)
](https://www.g2.com/products/azure-data-factory/reviews?filters%5Bsentiment_snippet%5D=1776886&qs=pros-and-cons#reviews)

Integrations

**AWS Data Pipeline**
Not enough data

**Azure Data Factory**
[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_b3390b4cc3d92e87d570895f7358c003/amazon-simple-email-service-amazon-ses.jpg "Product Avatar Image")

Amazon

](https://www.g2.com/products/amazon-simple-email-service-amazon-ses/reviews)[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_f176b4154a751d10150daa67a57b7dc5/azure-blob-storage.jpg "Product Avatar Image")

Azure Blob Storage

](https://www.g2.com/products/azure-blob-storage/reviews)[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_f176b4154a751d10150daa67a57b7dc5/azure-data-lake-store.jpg "Product Avatar Image")

Azure Data Lake Store

](https://www.g2.com/products/azure-data-lake-store/reviews)[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_13aba37ae908d9cf29a2452925257ccc/azure-databricks.jpeg "Product Avatar Image")

Azure Databricks

](https://www.g2.com/products/azure-databricks/reviews)[
View all
](https://www.g2.com/products/azure-data-factory/integrations)

Ratings

Meets Requirements

**AWS Data Pipeline**

9.1

9.118

**Azure Data Factory**

9.1

9.179

Ease of Use

**AWS Data Pipeline**

8.6

8.618

**Azure Data Factory**

8.9

8.981

Ease of Setup

**AWS Data Pipeline**

6.9

6.97

**Azure Data Factory**

9.0

9.046

Ease of Admin

**AWS Data Pipeline**

6.9

6.97

**Azure Data Factory**

8.6

8.632

Quality of Support

**AWS Data Pipeline**

8.3

8.317

**Azure Data Factory**

8.8

8.874

Has the product been a good partner in doing business?

**AWS Data Pipeline**

7.4

7.47

**Azure Data Factory**

9.0

9.031

Product Direction (% positive)

**AWS Data Pipeline**

6.1

6.118

**Azure Data Factory**

9.8

9.875

Features

ETL Tools[Hide 57 FeaturesShow 57 Features](javascript:void(0);)

Not enough data

9.0

63

Management

Reporting

Not enough data

8.6(won by default)

50

Auditing

Not enough data

8.4(won by default)

46

Functionality

Extraction

Not enough data

9.2(won by default)

57

Transformation

Not enough data

9.1(won by default)

55

Loading

Not enough data

9.4(won by default)

52

Automation

Not enough data

9.2(won by default)

54

Scalability

Not enough data

9.1(won by default)

51

Non-Relational Transformations

Not enough data

Not enough data

Data Extraction

Not enough data

Not enough data

Additional Functionality

Data Mapping

Not enough data

Not enough data

Monitoring

Not enough data

Not enough data

Charting

Not enough data

Not enough data

Integration Management

Not enough data

Not enough data

Reporting/Analytics

Not enough data

Not enough data

Ad hoc Analysis

Not enough data

Not enough data

Access Controls/Permissions

Not enough data

Not enough data

API

Not enough data

Not enough data

Match & Merge

Not enough data

Not enough data

Real-Time Monitoring

Not enough data

Not enough data

Metadata Management

Not enough data

Not enough data

Pipeline Management

Not enough data

Not enough data

Job Scheduling

Not enough data

Not enough data

Dashboard Creation

Not enough data

Not enough data

Data Storage Management

Not enough data

Not enough data

Multiple Data Sources

Not enough data

Not enough data

Data Import/Export

Not enough data

Not enough data

Generative AI

Not enough data

Not enough data

Data Quality Control

Not enough data

Not enough data

Data Connectors

Not enough data

Not enough data

Customizable Reports

Not enough data

Not enough data

Single Sign On

Not enough data

Not enough data

Version Control

Not enough data

Not enough data

Visual Analytics

Not enough data

Not enough data

Accounting Integration

Not enough data

Not enough data

Real-Time Data

Not enough data

Not enough data

eCommerce Management

Not enough data

Not enough data

AI Copilot

Not enough data

Not enough data

CRM

Not enough data

Not enough data

Data Visualization

Not enough data

Not enough data

SSL Security

Not enough data

Not enough data

Search/Filter

Not enough data

Not enough data

Real-Time Analytics

Not enough data

Not enough data

Data Capture and Transfer

Not enough data

Not enough data

Collaboration Tools

Not enough data

Not enough data

Performance Management

Not enough data

Not enough data

Data Synchronization

Not enough data

Not enough data

Drag & Drop

Not enough data

Not enough data

Data Replication

Not enough data

Not enough data

Activity Dashboard

Not enough data

Not enough data

Database Support

Not enough data

Not enough data

Workflow Management

Not enough data

Not enough data

Alerts/Notifications

Not enough data

Not enough data

Predictive Analytics

Not enough data

Not enough data

Data Migration

Not enough data

Not enough data

Third-Party Integrations

Not enough data

Not enough data

Reporting & Statistics

Not enough data

Not enough data

Data Analysis Tools

Not enough data

Not enough data

User Insights

Reviewers' Company Size

[![AWS Data Pipeline](https://images.g2crowd.com/uploads/product/hd_favicon/1528476492/aws-data-pipeline.svg "AWS Data Pipeline")](https://www.g2.com/products/aws-data-pipeline/reviews)

AWS Data Pipeline

Small-Business(50 or fewer emp.)

14.3%

Mid-Market(51-1000 emp.)

61.9%

Enterprise(\> 1000 emp.)

23.8%

[![Azure Data Factory](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_f176b4154a751d10150daa67a57b7dc5/azure-data-factory.jpg "Azure Data Factory")](https://www.g2.com/products/azure-data-factory/reviews)

Azure Data Factory

Small-Business(50 or fewer emp.)

12.5%

Mid-Market(51-1000 emp.)

29.2%

Enterprise(\> 1000 emp.)

58.3%

Small-Business

(50 or fewer emp.)

14.3%

12.5%

Mid-Market

(51-1000 emp.)

61.9%

29.2%

Enterprise

(\> 1000 emp.)

23.8%

58.3%

Reviewers' Industry

[![AWS Data Pipeline](https://images.g2crowd.com/uploads/product/hd_favicon/1528476492/aws-data-pipeline.svg "AWS Data Pipeline")](https://www.g2.com/products/aws-data-pipeline/reviews)
AWS Data Pipeline

Computer Software

23.8%

Telecommunications

14.3%

Information Technology and Services

9.5%

Financial Services

9.5%

Sports

4.8%

Other

38.1%

[![Azure Data Factory](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_f176b4154a751d10150daa67a57b7dc5/azure-data-factory.jpg "Azure Data Factory")](https://www.g2.com/products/azure-data-factory/reviews)
Azure Data Factory

Information Technology and Services

30.9%

Computer Software

12.4%

Consulting

6.2%

Financial Services

5.2%

Airlines/Aviation

4.1%

Other

41.2%

FAQs

## AWS Data Pipeline vs Azure Data Factory FAQs

Generated using AI

Last updated: August 14, 2026

### What is the difference between AWS Data Pipeline vs Azure Data Factory?

Azure Data Factory stands out from AWS Data Pipeline with a higher G2 rating, stronger support, and a more favorable Ease of Setup score, while AWS Data Pipeline's largest reviewer segment is Mid-Market and Azure Data Factory's is Enterprise.

| [AWS Data Pipeline](https://www.g2.com/products/aws-data-pipeline/reviews) | [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) |
| --- | --- |
| 4.1/5 (24 reviews) | 4.6/5 (101 reviews) |
| Mid-Market | Enterprise |
| 6.9 | 9.0 |
| 8.3 | 8.8 |
| Easy to run Spark jobs and integrates well with AWS services | Data integration and ease of use (7 all-time mentions each) |

### How do the pricing models of AWS Data Pipeline and Azure Data Factory compare?

Azure Data Factory is rated higher for value, with reviewers expressing greater satisfaction with its pricing and cost-effectiveness compared to AWS Data Pipeline.

- **AWS Data Pipeline:** Reviewers note it is low cost and only charged when used, but some mention the license version is expensive.
- **Azure Data Factory:** In recent reviews, many highlight its affordability and cost-effectiveness, though a few mention costs can add up with complex or frequent pipelines.
- **Switching reasons:** Reviewers cite Azure Data Factory's scalability and integration capabilities as reasons for preferring it over other ETL tools.

### What are the best alternatives to AWS Data Pipeline and Azure Data Factory?

The top three alternatives to AWS Data Pipeline and Azure Data Factory are Fivetran, Apache NiFi, and SnapLogic.

| Product | G2 Rating (reviews) | Largest Segment | Pricing Insight | Top Reviewer-Cited Strength |
| --- | --- | --- | --- | --- |
| [AWS Data Pipeline](https://www.g2.com/products/aws-data-pipeline/reviews) | 4.1/5 (24) | Mid-Market | Low cost, but license version can be expensive | Easy to run Spark jobs and integrates well with AWS services |
| [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) | 4.6/5 (101) | Enterprise | Affordable and cost-effective, but costs can add up with complex pipelines | Data integration and ease of use (7 all-time mentions each) |
| [Fivetran](https://www.g2.com/products/fivetran/reviews) | 4.3/5 (828) | Mid-Market | — | — |
| [Apache NiFi](https://www.g2.com/products/apache-nifi/reviews) | 4.2/5 (26) | Enterprise | — | — |
| [SnapLogic](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) | 4.4/5 (406) | Enterprise | — | — |

### Which ETL Tools features should I prioritize when comparing AWS Data Pipeline and Azure Data Factory?

Buyers should prioritize Ease of Setup, Integration Capabilities, Data Integration, Scalability, and Debugging Experience when comparing AWS Data Pipeline and Azure Data Factory.

- **Ease of Setup:** Azure Data Factory scores 9.0, AWS Data Pipeline scores 6.9.
- **Integration Capabilities:** Azure Data Factory has 6 all-time mentions for integrations and 6 for connectors; AWS Data Pipeline reviewers cite strong AWS service integration.
- **Data Integration:** Azure Data Factory has 7 all-time mentions for data integration; AWS Data Pipeline is noted for easy data movement between AWS sources.
- **Scalability:** Azure Data Factory has 5 all-time mentions for scalability.
- **Debugging Experience:** Azure Data Factory has 5 all-time mentions for debugging difficulty and 4 for difficult debugging.

### What are the pros and cons of AWS Data Pipeline vs Azure Data Factory?

Azure Data Factory's headline strength is its data integration and ease of use, while AWS Data Pipeline is praised for its integration with AWS services and Spark job orchestration.

- **AWS Data Pipeline strengths:** Easy to run Spark jobs, integrates well with AWS services, drag-and-drop UI, and automation for batch processing.
- **AWS Data Pipeline trade-offs:** Lacks on-demand job execution, limited to AWS ecosystem, maintenance mode affects feature updates, and setup can be complex for customized ETL.
- **Azure Data Factory strengths:** Data integration (7 all-time mentions), ease of use (7), connectors (6), integrations (6), scalability (5), automation (4), and flexibility (4).
- **Azure Data Factory trade-offs:** Debugging difficulty (5 all-time mentions), expensive for complex/frequent pipelines (4), feature limitations (4), and complexity in managing large or complex workflows (3).

### Is AWS Data Pipeline or Azure Data Factory better for small businesses?

Azure Data Factory is the better fit for small businesses, with reviewers highlighting its affordability, ease of use, and scalability for organizations of all sizes.

- **AWS Data Pipeline:** Largest reviewer segment is Mid-Market; reviewers note its low cost and reliability, but mention setup complexity and AWS-centric integrations.
- **Azure Data Factory:** Largest reviewer segment is Enterprise, but recent reviews emphasize its suitability for small businesses due to low cost, user-friendly interface, and broad integration options.

### Which ETL Tools platform has better integrations?

Azure Data Factory is favored by reviewers for integrations, with more all-time mentions and a broader range of supported connectors.

- **AWS Data Pipeline:** Reviewers highlight strong integration with AWS services, especially EMR and S3, but note limited support for non-AWS platforms.
- **Azure Data Factory:** Databricks (12 all-time mentions), Azure Blob Storage (3), and Azure Databricks (2); 6 all-time mentions for integrations and 6 for connectors, with reviewers praising its ability to connect to a wide range of data sources and services.

### How do AWS Data Pipeline and Azure Data Factory compare on customer support?

Azure Data Factory leads AWS Data Pipeline on Quality of Support by 0.5 points, a material difference in reviewer satisfaction.

- **AWS Data Pipeline:** Reviewers rate support at 8.3, with mixed experiences; some cite timely assistance, while others mention slow response due to maintenance mode.
- **Azure Data Factory:** Reviewers rate support at 8.8, with many citing responsive and helpful support, especially for setup and troubleshooting, though a few mention challenges with complex issues.

### Which is easier to implement, AWS Data Pipeline or Azure Data Factory?

Azure Data Factory is easier to implement than AWS Data Pipeline, with a 2.1-point lead in Ease of Setup and a 1.8-point lead in Ease of Admin.

- **AWS Data Pipeline:** Reviewers describe setup as straightforward for AWS-centric workflows but note complexity for customized ETL and initial configuration.
- **Azure Data Factory:** Reviewers consistently praise its drag-and-drop interface, low-code setup, and user-friendly onboarding, with many citing quick implementation and ease of administration.

Alternatives

**AWS Data Pipeline Alternatives**

 ![Apache NiFi](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_d126f094f8a50e553d82706d908d28c4/apache-nifi.jpg "Apache NiFi")

[
Apache NiFi
](/products/apache-nifi/reviews)

 ![Fivetran](https://images.g2crowd.com/uploads/product/hd_favicon/1526948884/fivetran.svg "Fivetran")

[
Fivetran
](/products/fivetran/reviews)

 ![Workato](https://images.g2crowd.com/uploads/product/hd_favicon/5e21242185438a3b63b0b3cc5eb921b0/workato.svg "Workato")

[
Workato
](/products/workato/reviews)

 ![Databricks](https://images.g2crowd.com/uploads/product/hd_favicon/135d1c9e39e19ef56dc8d0bf90fce20f/databricks.svg "Databricks")

[
Databricks
](/products/databricks/reviews)

**Azure Data Factory Alternatives**

 ![Fivetran](https://images.g2crowd.com/uploads/product/hd_favicon/1526948884/fivetran.svg "Fivetran")

[
Fivetran
](/products/fivetran/reviews)

 ![SnapLogic Agentic Integration and Applied AI Platform](https://images.g2crowd.com/uploads/product/hd_favicon/912d8776f7f16fdcaacfee88f3cc18a9/snaplogic-agentic-integration-and-applied-ai-platform.svg "SnapLogic Agentic Integration and Applied AI Platform")

[
SnapLogic Agentic Integration and Applied AI Platform
](/products/snaplogic-agentic-integration-and-applied-ai-platform/reviews)

 ![dbt](https://images.g2crowd.com/uploads/product/hd_favicon/fb5962d21f726bb78733c336e00ac3ef/dbt.svg "dbt")

[
dbt
](/products/dbt/reviews)

 ![AWS Glue](https://images.g2crowd.com/uploads/product/hd_favicon/1528476465/aws-glue.svg "AWS Glue")

[
AWS Glue
](/products/aws-glue/reviews)

## AWS Data Pipeline vs Azure Data Factory

When assessing the two solutions, reviewers found Azure Data Factory easier to use, set up, and administer. Reviewers also preferred doing business with Azure Data Factory overall.

- AWS Data Pipeline and Azure Data Factory both meet the requirements of our reviewers at a comparable rate.
- When comparing quality of ongoing product support, reviewers felt that Azure Data Factory is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Azure Data Factory over AWS Data Pipeline.