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Kestrel vs NSQ: What are the differences?
What is Kestrel? Simple, distributed message queue system. Kestrel is based on Blaine Cook's "starling" simple, distributed message queue, with added features and bulletproofing, as well as the scalability offered by actors and the JVM.
What is NSQ? A realtime distributed messaging platform. NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.
Kestrel and NSQ belong to "Message Queue" category of the tech stack.
Some of the features offered by Kestrel are:
- Written by Robey Pointer
- Starling clone written in Scala (a port of Starling from Ruby to Scala)
- Queues are stored in memory, but logged on disk
On the other hand, NSQ provides the following key features:
- support distributed topologies with no SPOF
- horizontally scalable (no brokers, seamlessly add more nodes to the cluster)
- low-latency push based message delivery (performance)
Kestrel and NSQ are both open source tools. NSQ with 15.6K GitHub stars and 2.03K forks on GitHub appears to be more popular than Kestrel with 2.8K GitHub stars and 326 GitHub forks.
I am looking into IoT World Solution where we have MQTT Broker. This MQTT Broker Sits in one of the Data Center. We are doing a lot of Alert and Alarm related processing on that Data, Currently, we are looking into Solution which can do distributed persistence of log/alert primarily on remote Disk.
Our primary need is to use lightweight where operational complexity and maintenance costs can be significantly reduced. We want to do it on-premise so we are not considering cloud solutions.
We looked into the following alternatives:
Apache Kafka - Great choice but operation and maintenance wise very complex. Rabbit MQ - High availability is the issue, Apache Pulsar - Operational Complexity. NATS - Absence of persistence. Akka Streams - Big learning curve and operational streams.
So we are looking into a lightweight library that can do distributed persistence preferably with publisher and subscriber model. Preferable on JVM stack.
Kafka is best fit here. Below are the advantages with Kafka ACLs (Security), Schema (protobuf), Scale, Consumer driven and No single point of failure.
Operational complexity is manageable with open source monitoring tools.
Pros of Kestrel
Pros of NSQ
- It's in golang29
- Distributed20
- Lightweight20
- Easy setup18
- High throughput17
- Publish-Subscribe11
- Scalable8
- Save data if no subscribers are found8
- Open source6
- Temporarily kept on disk5
- Simple-to use2
- Free1
- Topics and channels concept1
- Load balanced1
- Primarily in-memory1
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Cons of Kestrel
Cons of NSQ
- Long term persistence1
- Get NSQ behavior out of Kafka but not inverse1
- HA1
