Users report that Apache Sqoop excels in data extraction capabilities, particularly with its ability to efficiently transfer large volumes of data from relational databases to Hadoop, with a strong focus on performance and speed.
Reviewers mention that Azure Data Factory shines in its transformation features, offering a user-friendly interface for data transformation tasks, which allows for complex data workflows without extensive coding knowledge.
G2 users highlight that Apache Sqoop has a robust automation feature, enabling scheduled data imports and exports, which is crucial for maintaining up-to-date data in Hadoop environments.
Users on G2 report that Azure Data Factory's scalability is a significant advantage, as it can handle varying workloads seamlessly, making it suitable for enterprises with fluctuating data processing needs.
Reviewers say that while Apache Sqoop has a strong ease of setup, Azure Data Factory's ease of use is often rated higher, with many users appreciating its intuitive drag-and-drop interface for building data pipelines.
Users mention that the quality of support for Azure Data Factory is generally perceived as superior, with many reviewers praising the responsiveness and helpfulness of the support team compared to Apache Sqoop's support experience.
Pricing
Entry-Level Pricing
Apache Sqoop
No pricing available
Azure Data Factory
No pricing available
Free Trial
Apache Sqoop
No trial information available
Azure Data Factory
No trial information available
Ratings
Meets Requirements
8.9
25
9.2
65
Ease of Use
8.7
25
8.9
66
Ease of Setup
9.1
11
9.2
31
Ease of Admin
9.2
11
8.6
23
Quality of Support
8.5
25
8.8
60
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