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How logstash is different than kafka?


Asked by Abel Roman on Dec 07, 2021 FAQ



Kafka has higher throughput, replication and reliability characteristics. Kafka is powerful than Logstash. Logstash is an open-source, data processing pipeline that allows to collect data from a number of resources, transform it and send it on the desired location Logstash is a tool to collect, process and forward events and log messages.
In this manner,
Logstash instances by default form a single logical group to subscribe to Kafka topics Each Logstash Kafka consumer can run multiple threads to increase read throughput. Alternatively, you could run multiple Logstash instances with the same group_id to spread the load across physical machines.
Besides, If you use the Logstash shipper and indexer architecture with Kafka, you can continue to stream your data from edge nodes and hold them temporarily in Kafka. As and when Elasticsearch comes back up, Logstash will continue where it left off, and help you catch up to the backlog of data.
Similarly,
To summarize the differences between Logstash and rsyslog: Logstash rsyslog Resource usage heavy light Inputs many fewer: files, all syslog flavors, Kafka Filters many fewer: GeoIP, anonymizing, etc. Though e ... Outputs many many (Elasticsearch, Kafka, SQL..) thoug ... 6 more rows ...
Indeed,
To understand how Kafka does these things, let’s dive in and explore Kafka’s capabilities from the bottom up. Kafka run as a cluster on one or more servers that can span multiple datacenters. The Kafka cluster stores streams of records in categories called topics. Each record consists of a key, a value, and a timestamp.