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Kafka Use Cases

Updated April 2021

Apache Kafka is a high-throughput, open source message queue used by Fortune 100 companies, government entities, and startups alike.

Part of Kafka’s appeal is its wide array of use cases.  In this post we will outline several of Kafka’s uses cases from event sourcing to tracking web activities to metrics and more.

Use Cases for Apache Kafka

#1 Kafka as a Message Broker

Kafka is one of the most popular messaging technologies because it is ideal for handling large amounts of homogeneous messages, and it is the right choice for instances with high throughput.  An additional part of its appeal is that it pairs well with big data systems such a Elasticsearch and Hadoop

#2 Kafka for Metrics

Kafka is used for monitoring operational data by producing centralized feeds of that data.  Operational data — anything from technology monitoring to security logs to supplier information to competitor tracking and more — can then be aggregated and monitored.

#3 Kafka for Event Sourcing

Because Kafka supports the collection of large amounts of log data, it can be a crucial component to any event management system, including SIEM (Security Information Event Management).

#4 Kafka for Commit Logs

Kafka can act as a pseudo commit-log, using it for replication of data between nodes and for restoring data on failed nodes.  For instance, if you are tracking device data for internet of things (IoT) sensors and discover an issue with your database not storing all data, then you can replay data to replace the missing information in the database.

#5 Kafka for Tracking Website Activity 

Because website activity creates large amounts of data, with many messages generated for each individual user page view and activity on the page, Kafka is integral to ensuring that data is sent to and received by the relevant database(s).


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Published by

Dattell - Kafka & Elasticsearch Support

Benefit from the experience of our Kafka, Pulsar, Elasticsearch, and OpenSearch expert services to help your team deploy and maintain high-performance platforms that scale. We support Kafka, Elasticsearch, and OpenSearch both on-prem and in the cloud, whether on stand alone clusters or running within Kubernetes. We’ve saved our clients $100M+ over the past six years. Without our guidance companies tend to overspend on hardware or purchase unnecessary licenses. We typically save clients multiples more money than our fees cost in addition to building, optimizing, and supporting fault-tolerant, highly available architectures.

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