Data Pipelines

 

The business demands of near real-time use cases, data enrichment on the fly, and near real-time analytics have altered the landscape of IT organizations and how they approach these needs. Today, more than ever, IT organizations have an abundance of choices as to how they will produce, transmit, and store data. 

At emergint, we help guide customers through the capability differences of technologies like Kafka, Batch, MQ Messaging, and many others to find the perfect solution to grow your business.  

Event-Streaming  

In an IT landscape traditionally dominated by databases, the idea of event-streaming may seem daunting. But when correctly implemented, an occasion of any size, whether it is a sale, shipment, customer sign-in, or any other component of your business, can become an event.  

Events can flow through technologies like Kafka, and become enriched in flight, or at their destination. They are then consumed in near-real time by other systems looking to make decisions or drive intelligence from an event.  

 

Batch Processing 

Batch processing is a proven method used to process store sales on a nightly basis and to transmit data from partners, or for any other process, looking at bulk load data on a semi-regular basis.  

 

While some batch processes are being replaced by more near real-time technologies, such as Kafka or MQ messaging technologies, we believe in its usefulness in modern architecture, depending on the business needs and systems producing and consuming data.  

Messaging with MQ 

A Messaging Queue is an added layer that allows multiple processes to communicate via various models. Using message queues to connect systems is a more reliable and robust way of sending messages back and forth. 

Depending on the implementation, it can be configured for things like guaranteed reliability, error reporting, security, discovery, and performance. 

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