Your details are moving? Ksolves’ Apache NiFi Services helps you with the move!

We are living in the generation where data is the foundation of our systems. It is basically the raw material that we fed to our applications. Keeping the data is a different thing, but the most complex and critical challenge is the movement of data. 

In this article, we will tell you how Ksolves along with Apache NiFi services can help you with moving your data.

Data transformation with Apache NiFi

First thing that should be in mind when we talk about data is that it shouldn’t be lost. The migration whether it is periodic or not should focus on this very fact. 

The universal rule says that the movement of data transformations and conversions of the information. For example, in data migration, in-service stops are required, which means stopping the source system until the target system is operational. In other cases, where the information is taken from external sources, the main focus is on the need for data transformation so it can fit our systems. 

When the data transfer is periodic, the most powerful and popular tool to perform the task is Apache NiFi. 

Apache NiFi is a data transformation and stream execution engine that is used for big data migration. In simple terms, It takes data from one source, passes it for processing to a process flow and delivers it to another source. 

Ksolves’ NiFi services: keep your data moving

Moving data is complex and doing it without any help can make it a burdensome process. A partner that can handle many things for you is always the right choice and Ksolves is best at doing it. As an Apache NiFi consulting company, we have a huge responsibility and all our Apache NiFi developers understand this. 

With Ksolves’ NiFi as a service you can quickly adapt data from other sources without any hassle. With a complete stack of Apache NiFi, we are experts in creating, dataflows and pipelines. Our highly customized services help you in moving and prioritizing your data so that your system won’t be overrun by it. 

Let us now move on to learn more about how NiFi makes your data move.

User Interface

The core strength of Apache NiFi is its web application. It allows you to design and visually configure the flow that carries the data. But, you can also operate in the process as well as monitor the status for the possible errors that have occurred.

You can also modify the flow during its execution just by stopping the flow from one end to make the changes. The data is queued for as long as the execution is resumed,

Processors

Apache NiFi is preloaded with processors which provide a certain functionality to the flow. These operations are-

• Interacting with data sources- It helps in uploading data from a wide range of formats like HDFS, FTP, SQL, and many others.

• Conversion of data- conversion to and from JSON, XML, Avro, CSV, etc.
• Information processing- Data joining, division, validation and transformation is carried out.
• Functionalities- Processors that can transfer data to other systems to perform other tasks.

Cluster Execution

Cluster execution is performed in order to achieve optimal performance. In this process various machines on which Apache NiFi is running come together to perform operations.

This execution is performed inside the Apache NiFi web interface. Also, inside the execution options, we have MiNiFi which is actually a NiFi derived project that helps us with a runtime with low requirements. 

In a Nutshell!

Well, now we can understand the importance of Apache NiFi. Since it is simple to use as it is completely integrated in a web application, and has power of capabilities with complex processor flows makes it the most preferred tool for transfer of data.

Ksolves is a leading Apache NiFi development company offering NiFi services in India and the USA. Our huge and talented team of Apache NiFi developers are specialized in providing customized and budget-friendly Apache NiFi services. If you have any further queries write to us in the comment section or give us a call for a free demo.