When comparing Kafka vs ODE, the Slant community recommends Kafka for most people. In the question“What are the best log management, aggregation & monitoring tools?” Kafka is ranked 8th while ODE is ranked 35th. The most important reason people chose Kafka is:
Kafka is optimized for supporting a huge number of users.
Specs
Ranked in these QuestionsQuestion Ranking
Pros
Pro Optimized for performance
Kafka is optimized for supporting a huge number of users.
Pro Native mirroring support
Kafka has native support for mirroring.
Pro Native compression support
Kafka has native support for compression.
Pro Scales easily
ODE instances are independent of each other, so they don't have to worry about a peer being added/removed. This allows the cluster to grow without any performance hit on the log aggregation. There is no redundancy built-in, but you can always use the forwarder to duplicate data. There is no sharding configuration or any other penalty that comes up with scaling a cluster. The clustering configuration is also very easy where you just list out peers for one of the node in order for it to run a search query on the whole cluster and merge the results. Scales better than any other open source log management tool out there.
Pro Add new parsers as you like
You can add any parser you want to ODE.
Pro Highly customizable
Pro Easy to use
Cons
Con Java is a resource hog
Java is a resource hog, making this far too slow unless you have money to throw at multiple servers with 1/2TB of ram.
Con Need Zookeeper
Kafka can only work with Zookeeper
Con Still in beta
Opallios ODE seems to be still in beta, as such there may be issues or missing features which are not yet implemented.