Apache NiFi is used mainly for ETL to get data from multiple sources and then load it into a data lake. For example, data from Ab Initio is extracted and then loaded to an S3 bucket. From the S3 bucket, that data is read again and then loaded into other data layers. Different data layers, such as raw and raw silver, all use Apache NiFi.

Apache NiFi has positively impacted the organization by making development really easy, allowing efficient design and development, and enabling code reuse which has reduced the development effort. Integration with Git is also really good for sharing code across teams. A reduction in development effort of about 30% has been observed.

The best features Apache NiFi offers include the ability to connect to any type of sources, which is a big advantage since most connectors are already available and do not need to be created. In transformation, it has a wide variety of transformations that can be used across big data and any kind of data, including JSON formatted data.

The connectors used most often include connecting to the Oracle database as the main focus and then connecting to log data, which have greatly benefited the team.

Improvements in the user interface to make it easier to use would be beneficial, and adding more security features would make Apache NiFi more secure and robust. Documentation and support could also be enhanced, as most support is usually received from users rather than from the product owners.

Apache NiFi has been used for more than five years.

Apache NiFi is stable.

The performance of Apache NiFi is really good. Based on the workload, more nodes can be added to make a bigger cluster, which enhances the cluster whenever needed. Apache NiFi's scalability is good and it is auto-scalable, which is pretty impressive.

Initially, customer support was contacted more often, but after understanding Apache NiFi better, not many issues have been faced. The customer support is really good, and they are helpful whenever concerns are posted, responding immediately.

Before Apache NiFi, StreamSets was used, and it was unsatisfactory as it consumed all the server resources and did not release them. After finding Apache NiFi, it became a preferred solution.

Apache NiFi provides a good return on investment, although specific cost details are not known since that is not an area of involvement. Feedback has been given to stakeholders that Apache NiFi is beneficial in development and does great work, indicating a positive return on investment.

Before choosing Apache NiFi, other options such as StreamSets, Teradata, Informatica Big Data version, and Glue were evaluated, but Glue was not chosen due to its high cost.

To train or onboard new team members to use Apache NiFi, the code has been modularized and processes have been documented really well, so when new team members are onboarded, they are asked to review that documentation to understand the processes and the modules that have been created. In a couple of days, once they go through all that material, they are up to speed.

In terms of flexibility and ease of use, Apache NiFi is more open compared to other ETL tools that have been used, such as Informatica and Teradata. It is open source with many contributors and can handle various data sources, including log data, structured, unstructured, and semi-structured data, unlike traditional ETL tools.

Tools such as Prometheus and Grafana are sometimes used to keep an eye on Apache NiFi server, and DataDog is also used along with it. Scaling Apache NiFi workloads is managed through auto-scaling.

To handle data security and compliance when using Apache NiFi, LDAP authentication is utilized, all clusters and nodes are kerberized, and single sign-on is used to authenticate. In transit, SSL encryption is used, and at rest, AES encryption is used, which is more than enough for the needs.

Apache NiFi is kept up to date by keeping an eye on new features that have been released, discussing them internally to assess if they need to be incorporated into development. If there are any gaps in the current version, an upgrade to the new version will be attempted.

Apache NiFi is a pretty good tool that meets most ETL needs, and in terms of performance and security, it is really good. After using it for quite some time without any issues, it is recommended as the number one tool for ETL. The overall review rating for Apache NiFi is 8 out of 10.

I have been using Apache NiFi for a couple of years now. My experience with Apache NiFi is that I have used it for a customer of ours who used that system to orchestrate ingestion processes from different sources into AWS. My main use case for Apache NiFi is data ingestion, so connecting to sources like APIs or different data lakes to get the data into S3. I manage more than 50 ingestion flows currently; some of them are quite small, dealing with a few megabytes a day, while others are multiple gigabytes a day and those are run daily, so we have a daily refresh of the sources.

Apache NiFi's best features include its plug-and-play solution, which means you don't need a lot of insight or knowledge to use it. The simplicity and plug-and-play approach of Apache NiFi has helped our team by allowing our customer to scale and build different ingestion flows, which previously needed additional development effort because custom solutions were required; now we just plug and play.

The features of Apache NiFi, including the integration capabilities to connect to different sources and monitoring with all the observability features, work really well for our team in obtaining the needed information. Apache NiFi has positively impacted our organization by making us a lot more productive; I would say development has significantly improved.

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.

I don't have any frustrations about how Apache NiFi can be improved; I'm pretty happy. I don't think there are needed improvements for Apache NiFi, particularly regarding the user interface, documentation, or performance.

I have been working in my current field for five years now.

Apache NiFi is indeed stable.

Apache NiFi's scalability works for us.

I haven't interacted with their customer support.

I have evaluated other options before choosing Apache NiFi, and I have used other options as well.

Apache NiFi is deployed in our organization using public cloud infrastructure. I purchased Apache NiFi through the AWS Marketplace. There are no improvements needed for Apache NiFi deployment on AWS, as the experience with that was pretty smooth.

I don't manage pricing, setup cost, or licensing for that customer, but I think they are pretty satisfied with it as well.

My advice for others looking into using Apache NiFi is that it's a good solution. I would rate this review 9 out of 10.

Apache NiFi is used for real-time and batch ingestion on data warehouse platforms. For example, Apache NiFi ingests all analytics from the e-commerce website into the data warehouse in the AWS Redshift database.

Speeding up projects with Apache NiFi has helped the organization by resulting in cost savings. A 30% reduction in cost was noticed as a specific metric regarding those savings.

The best feature of Apache NiFi is the simplicity of the tools because it is a drag-and-drop tool. The simplicity of Apache NiFi's tools helps by speeding up all the implementation process. Apache NiFi is also used to speed up projects in order to gain more projects in less time.

Apache NiFi is a good product as it is currently.

Apache NiFi has been used for a long time, five years in different projects.

Apache NiFi is stable.

The scalability of Apache NiFi is good because it is simple to scale up the resources.

The customer support for Apache NiFi is fine. I would rate the customer support of Apache NiFi a 10 on a scale of 1 to 10.

Positive

A custom solution implemented with Python was previously used before switching to Apache NiFi. The decision was made to switch from the custom Python solution to Apache NiFi to simplify all the deployment.

Apache NiFi was purchased through the AWS Marketplace.

A return on investment has not been observed, and it is not possible to share these metrics.

The experience with pricing, setup cost, and licensing was fine, as the integration with the AWS Marketplace was very good. The pricing in Italy is considered a little bit high, but the product is worth it.

Other options were not evaluated before choosing Apache NiFi.

Apache NiFi receives a rating of 9 out of 10. This rating of 9 out of 10 for Apache NiFi was chosen because of the documentation and the support of the product. The advice for others looking into using Apache NiFi is to test the solution with a POC and then go to production in a quick way.