Kafka Streams – A First Impression

Most stream processing frameworks require that you have processing infrastructure available or require the use of a 3rd party service in order to accomplish your stream processing. The overhead associated with these sorts of solutions, either the operational effort required for the infrastructure or direct cost, can sometimes be prohibitive to getting a project off the ground. Kafka Streams has taken a different approach and does not require any external infrastructure beyond Kafka. Instead of relying on this external infrastructure, Kafka Streams integrates into your project as a normal library.  This approach minimizes the upfront cost and reduces the adoption penalty (i.e. it’s easy to use for just one project) but it does come with some trade-offs.

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Kafka Streams – A First Impression

Kafka Streams – A First Impression

Most stream processing frameworks require that you have processing infrastructure available or require the use of a 3rd party service in order to accomplish your stream processing. The overhead associated with these sorts of solutions, either the operational effort required for the infrastructure or direct cost, can sometimes be prohibitive to getting a project off the ground. Kafka Streams has taken a different approach and does not require any external infrastructure beyond Kafka. Instead of relying on this external infrastructure, Kafka Streams integrates into your project as a normal library. This approach minimizes the upfront cost and reduces the adoption penalty (i.e. it’s easy to use for just one project) but it does come with some trade-offs.

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Graph DB Shootout 2.0 at DataDay Seattle

Graph DB Shootout 2.0 at DataDay Seattle

Graph Database Shootout 2.0 slide deck from DataDay Seattle. Given by Josh Perryman on July 23. 2016. After a quick review of the original Graph Database shootout presentation given in Austin earlier in the year, I turn attention to two popular graph database engines: Neo4j and DataStax’s DSE Graph. I look at the features added for each in the past 6 months, and walk through basic data load and query writing use cases.

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