Compare Apache NiFi and Apache Sqoop 
- Users report that Apache NiFi excels in data flow automation, with features like "Data Provenance" allowing for easy tracking of data lineage, which enhances transparency and debugging capabilities.
- Reviewers mention that Apache Sqoop shines in its ability to efficiently transfer large volumes of data between Hadoop and relational databases, particularly highlighting its "Import" and "Export" functionalities as critical for ETL processes.
- G2 users indicate that while both products have strong extraction capabilities, Apache NiFi's "Processor" architecture offers more flexibility and customization options, making it easier to adapt to specific data workflows.
- Users on G2 report that Apache Sqoop's ease of setup is a significant advantage, with many reviewers noting that its command-line interface is straightforward for users familiar with SQL, whereas NiFi's UI may require a steeper learning curve.
- Reviewers say that Apache NiFi's "User Interface" is highly intuitive, allowing for drag-and-drop functionality, which enhances user experience and reduces the time needed for onboarding new team members.
- Users mention that while both tools have solid support, Apache Sqoop receives higher marks for quality of support, with many users praising the responsiveness and helpfulness of the community and documentation available.
It's open-source and community-supported, you can build anything you want, from simple file ingestion to Kafka, S3, etc... The ability to create Process groups and isolate your workloads. The number of prebuilt processors. The flow-based programming comes...
Tracking lineage at a row level is important in data lake ingestion implementation. Can Lineage be controlled at per-row level? Batch transformation performance. Need to Benchmark. May require Kafka
Essay to use, good is security, and fast data transferring between source to destination.
Nothing as such, I found the tool very useful
It's open-source and community-supported, you can build anything you want, from simple file ingestion to Kafka, S3, etc... The ability to create Process groups and isolate your workloads. The number of prebuilt processors. The flow-based programming comes...
Essay to use, good is security, and fast data transferring between source to destination.
Tracking lineage at a row level is important in data lake ingestion implementation. Can Lineage be controlled at per-row level? Batch transformation performance. Need to Benchmark. May require Kafka
Nothing as such, I found the tool very useful
