5 Factors to Consider When Choosing a Stream Processing Engine

Stream processing engines can make or break any organization’s future. But the question is are you using the right stream processing engine? You might be as well, but have you really examined the stream engines and compared them. If not, this blog is for you. 

Ksolves being one the leading development company offers many of the popular streaming engines used today. We know the specific demands of our clients and will always guide and suggest to you the most optimal one. 

In this blog we will define the five factors that you should consider to get a better understanding of the right engine for your business. 

• Functional Aspects

Each stream processing engine has its own unique set of functional aspects. One such example is the approach taken by development communities at the inception. It revolves around the goal for which the engine is designed. Every engine is originated to serve a specific purpose.

More functional aspects to consider are streaming model and time support. Do you need a stateful model or a stateless one would do? Can that engine differentiate between time and processing time? Ksolves will help you in answering these questions and narrowing down the options for you.

• Development Control

 A very common phenomenon today is importing data from one or many systems, transforming it and then exporting results to another system. And hence these activities need to become more automated. When you are evaluating any stream processing engine, you should consider their abstraction capabilities as well. Will your engine let your data engineers focus on logic? Ask this question before you go for any option.

• Implementation and Management

Every business today needs a stream processing engine that can help them in moving beyond the idea and development stage and can process real-time data at a large volume. While choosing the right option, evaluate the engine’s delivery guarantee and know about the latency, throughput, correctness, and fault tolerance of message delivery. 

You also need to check the stage management capabilities of any engine that you choose. Does the engine provide a scheduler? Does it offer fault tolerance and resilience? But also keep in mind that not all stream processing engines don’t offer the same level of built-in fault tolerance. 

• Enterprise Adoption

The ease of Enterprise adoption is the biggest factor while selecting any stream processing engine. The most effective solutions are always the ones that can be easily adopted across enterprises. Look for those engines that are not limited in their deployment options.

Apart from deployment models, you should also consider the community maturity and quality of documentation of any engine. Overlooking these factors could result in hindered productivity.

• Enterprise Operations

Every business is different and so are their requirements. You need to choose an engine that can seamlessly integrate into your organization’s security framework while providing comprehensive monitoring and metrics and is scalable enough to meet business demands. To establish a long-term solution you need to be future-ready. 

Another factor is scalability. We all know that streaming workflows are usually multi-modal and unbalanced. It makes scaling capabilities difficult. Some engines have auto-scaling capabilities which can make your task easier.

Choosing the right engine with Ksolves

Do you want to know what we recommend to our clients? Our simple answer is Apache NiFi. We are saying so because Apache NiFi is based on Enterprise Integration Patterns (EIP) and comes with an intuitive graphical interface that makes it easy to design data flows. It also supports various input sources that include static and streaming data sets. 

Ksolves is one of the best architects of Apache NiFi and a leading Big Data consulting company with an experienced team of NiFi developers with years of experience in delivering budget-friendly NiFi solutions.

For more information on Apache NiFi and Big Data, write to us in the comment section below or give us a call!