Compare Apache NiFi and Informatica PowerCenter 
- Users report that Informatica PowerCenter excels in data transformation capabilities, with a score of 9.1, while Apache NiFi follows closely with a score of 9.3. Reviewers mention that PowerCenter's robust ETL (Extract, Transform, Load) processes are particularly beneficial for complex data workflows.
- Reviewers mention that Apache NiFi shines in automation features, scoring 9.3 compared to Informatica's 8.5. Users on G2 appreciate NiFi's ability to automate data flows seamlessly, which enhances operational efficiency.
- G2 users highlight that Informatica PowerCenter offers superior data security with a score of 9.2, while NiFi scores slightly lower at 7.5. Reviewers say that PowerCenter's comprehensive security features provide peace of mind for enterprises handling sensitive data.
- Users say that both products perform well in reporting, with PowerCenter scoring 8.9 and NiFi at 9.3. However, reviewers mention that NiFi's reporting capabilities are more user-friendly, making it easier for non-technical users to generate insights.
- Reviewers mention that Informatica PowerCenter has a more complex setup process, scoring 7.4, while NiFi's ease of setup is rated at 9.0. Users report that NiFi's intuitive interface allows for quicker deployment and less technical overhead.
- Users on G2 indicate that while both products have strong data visualization features, PowerCenter's score of 8.8 is slightly lower than NiFi's 9.2. Reviewers say that NiFi's visualization tools are more versatile and easier to use for real-time data monitoring.
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
- GUI based Power Data Integrator - Best in class with tight integration with industry leading databases like Oracle & Teradata - Always leading with cutting edge features like JSON webservice support, CDC, Cloud, Data Virtualization
Mdm is bit complex to understand the technology
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...
- GUI based Power Data Integrator - Best in class with tight integration with industry leading databases like Oracle & Teradata - Always leading with cutting edge features like JSON webservice support, CDC, Cloud, Data Virtualization
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
Mdm is bit complex to understand the technology
