By accepting this, NSQ is a much more traditional buffered messaging system.

See features & guarantees. Which is a major missing feature when comparing it to Kafka.

Get NSQ behavior out of Kafka but not inverse. In general, NATS and Redis are better suited to smaller messages (well below 1MB), in which latency tends to be sub-millisecond up to four nines.NATS is not HTTP, it’s its own very simple text-based protocol, RPC-like. This is done/initiated from the client itself & there are complex situations that can arise due to this (e.g.

— look at the dominance of Golang here! Pulsar — ConsMessageId concept tied to BookKeeper — consumers cannot easily position itself on the topic compared to Kafka offset which is a continuous sequence of numbers.A reader cannot easily read the last message on the topic — need to skim through all the messages to the end. Pulsar — ProsFeature rich — persistent/nonpersistent topics, multitenancy, ACLs, Multi-DC replication etc.More flexible client API that is easier to use — including CompletableFutures, fluent interfaces etc.Java client components are thread-safe — a consumer can acknowledge messages from different threads. Compare the number of customers of NATS and NSQ Industry NATS Customers NSQ Customers; Software: 13: 2 Internet: 6: 1 … NATS is useful when raw performance is a priority.Both NATS and NSQ queues support for per-message TTL, for pruning time-sensitive messages. And this costs several hundreds of milliseconds of latency. In other words: A single slow consumer can block a significant portion of the queue. Architecturally, that’s because NATS doesn’t have a persistence layer to use to store data durably.While Kafka does have a persistence layer (using storage on the cluster).To fully guarantee that a message won’t be lost, it looks like you need to declare the queue as durable + to mark your message as persistent + use publisher confirms.


You will now have one consumer C1 which is idle, while C2 is doing work. But a hard loss of a node means that those messages that have not been delivered can be lost as there is no promise they are published somewhere else. # References: [1] [A high performance C++ (14) messaging lib for latency sensitive software development : cpp] https://www.reddit.com/r/cpp/comments/894y48/a_high_performance_c_14_messaging_lib_for_latency/, [Modern Open Source Messaging: Apache Kafka, RabbitMQ and NATS in Action — Richard Seroter’s Architecture Musings]https://seroter.wordpress.com/2016/05/16/modern-open-source-messaging-apache-kafka-rabbitmq-and-nats-in-action/, [The Open Source Messaging Landscape]https://www.slideshare.net/rseroter/the-open-source-messaging-landscape, [Is NATS.IO a real alternative to Kafka? No transaction No enhanced delivery modesNo enterprise queueing. https://github.com/nats-io/nats-streaming-serverNATS was originally built with Ruby and achieved a respectable 150k messages per second. # Apache Pulsar (pulsar.incubator.apache.org): JavaIt was designed at Yahoo as a high-performance, low latency, scalable, durable solution for both pub-sub messaging and message queuing. It works as a publish-subscribe engine, but you can also get synthetic queuing.

Pulsar gives you one system for both streaming and queuing, with the same high performance, using a unified API. Kafka runs on JVM (Scala to be specific). Once deployment, Cons:Fire and forget, no persistence: NATS doesn’t do persistent messaging; if you’re offline, you don’t get the message. Kafka — ConsConsumer cannot acknowledge message from a different threadNo multitenancyNo robust Multi-DC replication — (offered in Confluent Enterprise)Management in a cloud environment is difficult. Unlike traditional enterprise messaging systems, NATS has an always-on dial tone that does whatever it takes to remain available.

Must say that the stability is great, even with larger payloads (over 10MB in size). It supports a variety of message routing paradigms. Cons:RabbitMQ’s high availability support is terrible. # RabbitMQ: RabbitMQ is a messaging engine that follows the AMQP 0.9.1 definition of a broker. Java client has Javadoc (https://pulsar.apache.org/api/client/), Community — 8 stackoverflow questions currently and https://pulsar.apache.org/powered-by/. And it comes with a shiny admin-dashboard, which NATS lacks. RabbitMQ can be deployed in a clustered fashion for performance, and mirrored fashion for high availability.

Once a previously dead node rejoins, it will start receiving messages.NATS in this case replaces something like HAProxy; a simple in-memory router of requests to backends. C1 can’t take any of C2’s work because it can only process its own partition. Kafka needs to think about partitions and offsets.It's better to think of Kafka as a distributed log service than a messaging broker, like the write ahead log in a database and not printf statements. — Bhagwan s. Soni — Medium]https://medium.com/@bhagwanssoni/apache-pulsar-is-it-a-kafka-killer-a7538afedd0b, # Good benchmarking report: [Benchmarking Message Queue Latency — Brave New Geek]https://bravenewgeek.com/benchmarking-message-queue-latency/[Benchmarking NATS Streaming and Apache Kafka — DZone Performance]https://dzone.com/articles/benchmarking-nats-streaming-and-apache-kafka, https://github.com/nats-io/nats-streaming-server, https://www.rabbitmq.com/persistence-conf.html, https://bitbucket.org/hmbd/hmbdc-rel/overview, https://bitbucket.org/hmbd/hmbdc-rel/wiki/Home, http://www.hummingbirdcode.net/p/blog-page.html, https://bitbucket.org/hmbd/hmbdc-rel/src/default/perf-sample.txt?fileviewer=file-view-default, http://open.syn3.nl/syn3/trac/default/wiki/projects/synapse, https://www.reddit.com/r/cpp/comments/894y48/a_high_performance_c_14_messaging_lib_for_latency/, https://seroter.wordpress.com/2016/05/16/modern-open-source-messaging-apache-kafka-rabbitmq-and-nats-in-action/, https://www.slideshare.net/rseroter/the-open-source-messaging-landscape, https://www.quora.com/Is-NATS-IO-a-real-alternative-to-Kafka-Who-used-it-in-a-production, https://stackshare.io/stackups/kafka-vs-nsq-vs-rabbitmq, https://stackshare.io/stackups/kafka-vs-nsq, https://news.ycombinator.com/item?id=11284489, https://aphyr.com/posts/315-jepsen-rabbitmq, https://simplydistributed.wordpress.com/2018/03/30/kafka-nats-random-notes/, https://www.businesswire.com/news/home/20180306005633/en/Apache-Pulsar-Outperforms-Apache-Kafka-2.5x-OpenMessaging, https://stackoverflow.com/questions/46048608/what-are-the-advantages-and-disadvantages-of-kafka-over-apache-pulsar, https://streaml.io/blog/pulsar-streaming-queuing, https://medium.com/@bhagwanssoni/apache-pulsar-is-it-a-kafka-killer-a7538afedd0b, https://bravenewgeek.com/benchmarking-message-queue-latency/, https://dzone.com/articles/benchmarking-nats-streaming-and-apache-kafka, A Python Study: Combining Candlestick Patterns with Technical Indicators, 10 Self-Taught Programmers Who Became Full-Time Developers, Airflow Series — Setting Up for GCP Projects, How I Accidentally Fell in Love with Coding. RabbitMQ does persist messages to disk. Incoming messages to the live nodes will still go to connected subscribers, and subscribers are expected to reconnect to the pool of available nodes. It is incredibly simple to operate at scale.Kafka’s performance and added guarantee come at the expense of being harder to operate.With Kafka you need a Zookeeper cluster in addition to your Kafka brokers. Kafka is more matured compared to Nats and performs very well with huge data streams.NATS Server has a subset of the features in Kafka as it is focused on a narrower set of use cases.

— Quora]https://www.quora.com/Is-NATS-IO-a-real-alternative-to-Kafka-Who-used-it-in-a-production, [RabbitMQ vs Kafka vs NSQ 2018 Comparison of Message Queue | StackShare] good side by side comparisonhttps://stackshare.io/stackups/kafka-vs-nsq-vs-rabbitmq, [Kafka vs NSQ 2018 Comparison of Message Queue | StackShare]https://stackshare.io/stackups/kafka-vs-nsq, [As someone who has used RabbitMQ in production for many years, you should rather… | Hacker News] https://news.ycombinator.com/item?id=11284489, [Jepsen: RabbitMQ]https://aphyr.com/posts/315-jepsen-rabbitmq, [NATS & Kafka: random notes | Simply Distributed] goodhttps://simplydistributed.wordpress.com/2018/03/30/kafka-nats-random-notes/, [Apache Pulsar Outperforms Apache Kafka by 2.5x on OpenMessaging Benchmark | Business Wire]https://www.businesswire.com/news/home/20180306005633/en/Apache-Pulsar-Outperforms-Apache-Kafka-2.5x-OpenMessaging, [What are the advantages and disadvantages of Kafka over Apache Pulsar — Stack Overflow]https://stackoverflow.com/questions/46048608/what-are-the-advantages-and-disadvantages-of-kafka-over-apache-pulsar, [Comparing Pulsar and Kafka: unified queuing and streaming] goodhttps://streaml.io/blog/pulsar-streaming-queuing, [Apache Pulsar : Is it a KAFKA Killer? Gain actionable insights about the buying patterns of NATS vs Consumers listen directly on queues, but publishers only know about “exchanges.” These exchanges are linked to queues via bindings, which specify the routing paradigm (among other things). Who used it in a production? It follows a standard store-and-forward pattern where you have the option to store the data in RAM, on disk, or both.
It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. It has file durability but only as a) an optimization to prevent message loss once memory runs out and b) as a consumer archive. Compare the number of customers of NATS and NSQ. Assume we have partitions 1 and 2. NATS doesn’t have replication, sharding or total ordering. * NATS vs. KafkaNATS recently joined CNCF (which host projects like Kubernetes, Prometheus etc. Consequently, RabbitMQ is a more “heavyweight” queuing solution and tends to pay an additional premium with.

NSQ - A realtime distributed messaging platform. Pros:Slogan: always on and available, dial toneConcise designLow CPU-consumingFast: Ahigh-velocity communication busHigh availabilityHigh scalabilityLight-weight: It’s tiny, just a 3MB Docker image! To sum up, Kafka aims for high throughput, Pulsar for low latency. https://bitbucket.org/hmbd/hmbdc-rel/overview http://www.hummingbirdcode.net/Design: https://bitbucket.org/hmbd/hmbdc-rel/wiki/Home Performance: http://www.hummingbirdcode.net/p/blog-page.htmlTake 8 bytes messages for example, well over 100M messages per second on a local machine (inter-thread or IPC) and more than 6M messages per second over Gigabit network.https://bitbucket.org/hmbd/hmbdc-rel/src/default/perf-sample.txt?fileviewer=file-view-defaultHmbdc may be not widely-used across the industry. NATS vs NSQ Customers by Industry. NATS - Lightweight publish-subscribe & distributed queueing messaging system.


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