How preferred is Kafka in Applications in terms of processing time without having Filters as in JMS selectors.










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  1. Kafka does not have any concept of filters at the brokers that can ensure – messages that are being picked up by a consumer matches some criteria. The filtering has to happen at the consumers (or applications). - So in this case there is an increase in the processing time at the client/consumer.


  2. In the case of JMS – if your messaging application needs to filter the messages it receives, you can use a JMS API message selector, which allows a message consumer to specify the messages it is interested in. Message selectors assign the work of filtering messages to the JMS provider rather than to the application. - So in this case there is an increase in the processing time at the JMS provider


Which of the above two proves to be better in terms of keeping the code clean and improving performance too?










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    1. Kafka does not have any concept of filters at the brokers that can ensure – messages that are being picked up by a consumer matches some criteria. The filtering has to happen at the consumers (or applications). - So in this case there is an increase in the processing time at the client/consumer.


    2. In the case of JMS – if your messaging application needs to filter the messages it receives, you can use a JMS API message selector, which allows a message consumer to specify the messages it is interested in. Message selectors assign the work of filtering messages to the JMS provider rather than to the application. - So in this case there is an increase in the processing time at the JMS provider


    Which of the above two proves to be better in terms of keeping the code clean and improving performance too?










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      1. Kafka does not have any concept of filters at the brokers that can ensure – messages that are being picked up by a consumer matches some criteria. The filtering has to happen at the consumers (or applications). - So in this case there is an increase in the processing time at the client/consumer.


      2. In the case of JMS – if your messaging application needs to filter the messages it receives, you can use a JMS API message selector, which allows a message consumer to specify the messages it is interested in. Message selectors assign the work of filtering messages to the JMS provider rather than to the application. - So in this case there is an increase in the processing time at the JMS provider


      Which of the above two proves to be better in terms of keeping the code clean and improving performance too?










      share|improve this question














      1. Kafka does not have any concept of filters at the brokers that can ensure – messages that are being picked up by a consumer matches some criteria. The filtering has to happen at the consumers (or applications). - So in this case there is an increase in the processing time at the client/consumer.


      2. In the case of JMS – if your messaging application needs to filter the messages it receives, you can use a JMS API message selector, which allows a message consumer to specify the messages it is interested in. Message selectors assign the work of filtering messages to the JMS provider rather than to the application. - So in this case there is an increase in the processing time at the JMS provider


      Which of the above two proves to be better in terms of keeping the code clean and improving performance too?







      apache-kafka activemq






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      asked Nov 13 '18 at 20:35









      Dhiraj GandhiDhiraj Gandhi

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          I don't think your question can be answered conclusively as the performance will ultimately depend on the actual implementation (i.e. which specific JMS provider is used) as well as the particular use-case (e.g. details like the number of clients, the message volume, how many messages match the filters, network speed, etc.).






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            I don't think your question can be answered conclusively as the performance will ultimately depend on the actual implementation (i.e. which specific JMS provider is used) as well as the particular use-case (e.g. details like the number of clients, the message volume, how many messages match the filters, network speed, etc.).






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              I don't think your question can be answered conclusively as the performance will ultimately depend on the actual implementation (i.e. which specific JMS provider is used) as well as the particular use-case (e.g. details like the number of clients, the message volume, how many messages match the filters, network speed, etc.).






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                I don't think your question can be answered conclusively as the performance will ultimately depend on the actual implementation (i.e. which specific JMS provider is used) as well as the particular use-case (e.g. details like the number of clients, the message volume, how many messages match the filters, network speed, etc.).






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                I don't think your question can be answered conclusively as the performance will ultimately depend on the actual implementation (i.e. which specific JMS provider is used) as well as the particular use-case (e.g. details like the number of clients, the message volume, how many messages match the filters, network speed, etc.).







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                answered Nov 13 '18 at 21:15









                Justin BertramJustin Bertram

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