

Apache NiFi and Amazon EC2 operate in data integration and cloud computing. Amazon EC2's extensive infrastructure gives it an advantage in scalability and performance.
Features: Apache NiFi offers an intuitive interface for visual data flow management, seamless data provenance, and robust security controls. Amazon EC2 provides high computing capacity, flexible storage, and comprehensive networking, with extensive cloud services suitable for dynamic computing needs.
Room for Improvement: Apache NiFi could enhance direct customer support options and expand scalability features. Improving its learning resources and community support would be beneficial. Enhancing its integration capabilities with a broader range of external tools could also be advantageous. Amazon EC2 could work on simplifying cost management tools to avoid unforeseen expenses. Enhancing the user interface for non-technical users and expanding documentation for better usability would be helpful. Improving the clarity of instance types and pricing plans for user awareness could be beneficial.
Ease of Deployment and Customer Service: Apache NiFi features a straightforward deployment process with its user-friendly configuration and robust data flow management, yet customer support is primarily community-driven. Amazon EC2 excels with extensive deployment options and strong infrastructure support, offering a wide range of support plans that ensure reliable performance and scalability.
Pricing and ROI: Apache NiFi, as an open-source tool, incurs lower initial setup costs, making it cost-effective for smaller enterprises, and provides significant ROI through improved data handling. Amazon EC2 uses a flexible, usage-based pricing model allowing for scaling of resources, which can lead to a higher ROI depending on utilization and management.
I would say I have saved more than a week with Amazon EC2 compared to my previous on-premises setup.
Thanks to improvements on both our side in how we run processes and enhancements to Apache NiFi, we have reduced the time commitment to almost not needing to interact with Apache NiFi except for minor queue-clearance tasks, allowing it to run smoothly.
It supports not just ETL but also ELT, allowing us to save significant time.
There may be return on investment based on the technology and easily moving our workloads onto Apache NiFi from our previous system.
The customer support is really good, and they are helpful whenever concerns are posted, responding immediately.
Customer support for Apache NiFi has been excellent, with minimal response times whenever we raise cases that cannot be directly addressed by logs.
I would rate the customer support of Apache NiFi a 10 on a scale of 1 to 10.
Depending on the workload we process, it remains stable since at the end of the day, it is just used as an orchestration tool that triggers the job while the heavy lifting is done on Spark servers.
Scaling up is fairly straightforward, provided you manage configurations effectively.
Based on the workload, more nodes can be added to make a bigger cluster, which enhances the cluster whenever needed.
I have seen Apache NiFi crashing at times, which is one of the issues we have faced in production.
Apache NiFi is stable in most cases.
I have heard from multiple people that if you have an Amazon EC2 instance running and you stop it, the billing continues unless you terminate the Amazon EC2 instance.
I think improvements can be made to Amazon EC2 by increasing the memory, offering more instance types, and including GPUs as mentioned in the keynote.
Apache NiFi should have APIs or connectors that can connect seamlessly to other external entities, whether in the cloud or on-premises, creating a plug-and-play mechanism.
The history of processed files should be more readable so that not only the centralized teams managing Apache NiFi but also application folks who are new to the platform can read how a specific document is traversing through Apache NiFi.
The initial error did not indicate it was related to memory or size limitations but appeared as a parsing error or something similar.
The pricing in Italy is considered a little bit high, but the product is worth it.
With the cloud, deployment is easy, and within a minute, we can deploy the server and give it to the developers so they can work on it right away after deployment.
Amazon EC2 offers flexibility.
Apache NiFi has positively impacted my organization by definitely bridging the gap between the on-premises and cloud interaction until we find a solution to open the firewall for cloud components to directly interact with on-premises services.
Development has improved with a reduction in time spent being the main benefit; before we needed a matter of days to create the ingestion flows, but now it only takes a couple of hours to configure.
The ease of use in Apache NiFi has helped my team because anyone can learn how to use it in a short amount of time, so we were able to get a lot of work done.
| Product | Market Share (%) |
|---|---|
| Amazon EC2 | 11.3% |
| Apache NiFi | 9.5% |
| Other | 79.2% |
| Company Size | Count |
|---|---|
| Small Business | 30 |
| Midsize Enterprise | 13 |
| Large Enterprise | 28 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 1 |
| Large Enterprise | 18 |
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.
Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate them from common failure scenarios.
We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.