

Apache NiFi and Amazon EC2 Auto Scaling operate in different domains but overlap in tasks related to orchestration and scalability. Apache NiFi demonstrates strength in data flow management and process complexity control, whereas Amazon EC2 Auto Scaling excels in server capacity scalability.
Features: Apache NiFi stands out with graphical flow-based programming, real-time analytics processing, and integration adaptability. Amazon EC2 Auto Scaling is recognized for its demand-based automatic scaling, comprehensive health checks, and broad AWS ecosystem integration.
Room for Improvement: Apache NiFi could enhance user-friendliness and simplify its setup for extensive deployment. Amazon EC2 Auto Scaling might improve by providing more cost-effective solutions for lower usage and enhancing its learning resources for new users.
Ease of Deployment and Customer Service: Apache NiFi's deployment can be intricate, necessitating expertise in data flow systems, which may challenge large-scale implementations. Amazon EC2 Auto Scaling leverages its AWS integration, facilitating smoother deployment with substantial support options.
Pricing and ROI: Apache NiFi, being open-source, offers low initial costs, although scaling can elevate expenses. Amazon EC2 Auto Scaling involves ongoing AWS-related operational costs yet delivers substantial ROI through efficient resource management and minimized wastage.
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.
I would rate the technical support of AWS a nine, as their team resolves issues effectively and meets our expectations.
They have very good support.
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.
The scaling feature appears to be embedded in the Amazon EC2 Auto Scaling price.
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.
Amazon EC2 Auto Scaling should automatically scale out systems during high demand and scale in new instances when demand decreases.
The stability of Amazon EC2 Auto Scaling rates a 10.
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.
Amazon should provide more detailed training materials for people who are just starting to work with Amazon EC2 Auto Scaling.
In enterprise environments such as healthcare or banking with numerous instances running different applications, customizable policies allow appropriate scaling.
The ability to ask questions about documentation through a chat interface would be valuable.
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.
It operates on a pay-as-you-go model, meaning if a machine is used for only an hour, the pricing will be calculated for that hour only, not the entire month.
In some projects, incorrect decisions were made by not consulting them first, resulting in higher setup and maintenance costs.
The pricing in Italy is considered a little bit high, but the product is worth it.
This pre-configuration makes on-demand scaling refined, and the configuration includes automatic traffic distribution because when the first system is overloaded, new incoming traffic is redirected to the newly created systems.
The service offers 99.9999% availability. We have high availability, and I haven't experienced any downtime during my usage periods.
The best feature I appreciate about Amazon EC2 Auto Scaling is its health check functionality; when a server becomes unreachable or enters an unhealthy state, it automatically triggers an alert, and the load balancer responds by spinning up a new server, ensuring that traffic is distributed effectively.
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 Auto Scaling | 7.7% |
| Apache NiFi | 9.5% |
| Other | 82.8% |

| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 9 |
| Large Enterprise | 27 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 1 |
| Large Enterprise | 18 |
Amazon EC2 Auto Scaling helps you maintain application availability and allows you to automatically add or remove EC2 instances according to conditions you define. ... Dynamic scaling responds to changing demand and predictive scaling automatically schedules the right number of EC2 instances based on predicted demand.
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