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Apache Kafka on Ubuntu

Websoft9 | Kafka 2.5.0-ubuntu 18.04

Linux/Unix, Ubuntu 18.04 - 64-bit Amazon Machine Image (AMI)

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External reviews

51 reviews
from G2

External reviews are not included in the AWS star rating for the product.


    Akib A.

Best tool for asynchronous communication

  • June 25, 2020
  • Review provided by G2

What do you like best?
Ability to use kafka as database, capability to handle large volume of data efficiently.
What do you dislike?
Very less monitoring tools , not all the scripts available for monitoring.
What problems are you solving with the product? What benefits have you realized?
We are using it extensively in our product, we are using it as messaging system and database both. We’re indexing our catalog data using kafka, sending data to our production environment using topics, importing data from external system over topics.


    Dhanish M.

Reliable and blazing fast message queue

  • June 16, 2020
  • Review verified by G2

What do you like best?
The ease of use as well as the number of various options that can be configured. It is also modular which allows you to plug in modules to increase functionality.
It is well supported by the community with lots of help available when stuck. Its also available as Docker images to make installation very easy.
What do you dislike?
The configuration options sometimes can get confusing and the documentation although very good is sometimes hard to follow.
Ensuring a configuration is correct and working as expected is not trivial as it is a network application and requires many clients to test it out. Adding extra modules might not make clients work correctly.
What problems are you solving with the product? What benefits have you realized?
I am using it as a distributed messaging system to share cyber threat events in real time. Benefits are that its open source and free to use, extremely reliable and fault tolerant making updates to network security trust-able and reliable. The added OAuth2 modules help in keeping the cluster secure and trustworthy.


    YOGESH B.

scalable data streaming

  • June 01, 2020
  • Review verified by G2

What do you like best?
scalable
data is partitioned
brokered
stable versions of kafka enables to upgrade the kafka at any time
Kafka parallelism at the topic level is very useful to achieve performance and scale to million requests per second
kafka has provided very well defined storage management, it provides many options to configure them by size & by time
What do you dislike?
load balancing requires all ips to be known by producer
When the kafka is hosted in any on prem environment, usually users does not want to expose all three ip address due to seccurity concerns. But kafka client needs all ip addresses of kafka cluster to load balance
Load time of the data when any node restart is huge when we have large data in kafka before restart
when one node goes down in cluster, it takes lot of time to rebalance
What problems are you solving with the product? What benefits have you realized?
data streaming from different IOT devices to processing engine, storm is connected to kafka and used to process and store in elastic search
we also stream logs with the system, events with in the system.
we also log from various devices, these logs are huge in number. almost millions for second.
Recommendations to others considering the product:
its a good platform for streaming your data in huge
it's easily scalable. Only issue when you start scaling is you have to mannually rebalance the partitions when you add a node or delete any existing nodes
be careful about systems when restarts are frequent because it takes considerable time to restart, how ever it is the best solution you can get among all opensource solutions available
Anthor aspect worth considering is its parallelism level, kafka is having pull mechanism to read the messages, partitins are per consumer, so it provides parallelsim at partitions level


    Civic & Social Organization

Advanced many-to-many streaming platform

  • May 14, 2020
  • Review provided by G2

What do you like best?
I like the simplicity of setup of Kafka broker in cluster mode. It permits to have a three powerful Kafka brokers by using even a single virtual low cost machine. The interaction with the cluster is quite simple and you can customize the topics functionalities by setting replication factors and main copy broker.
I like also the flexibility of Kafka. It can be used for managing high quantity of messages from multiple sensors, but also to stream a single big video to multiple subscribers.
What do you dislike?
I have not found anything that I dislike until now. Maybe the confluent support can be improved, since they offer only support for payed Confluent licenses and not for on-premises Kafka installation.
What problems are you solving with the product? What benefits have you realized?
I can share messages with many subscribers. I can gather data from a multiplicity of sensors. I can scale up horizontally with low cost machines.
Recommendations to others considering the product:
Kafka is really complete and permits to connect several producers with many customers. It is quite simple to be installed and the resource consumption is quite small.


    Yogesh B.

Best Streaming Queue/Topic

  • May 07, 2020
  • Review verified by G2

What do you like best?
Kafka is known the best streaming platform, it has the capability to handle data in pull mechanism makes it highly performant. Kafka provides capabilities to segregate data via topics, it supports binary data and text data. It has the capability to distribute data to partitions, a notion of shards
Kafka has consumer - kafka streams which is built on the principles of kafka to give better performance
we considered replacing storm with kafka streams and could achieve all the required functionalities
kafka provides various tune ups to achieve HA
What do you dislike?
One thing I observed is we can not switch off replication in multi node setup. suppose say i want only load distribution but its okay if i lose data. I dont want any replication. If any partition assigned node goes down, kafka should identify and reassign the partitions at some point to other nodes instead it goes on toss expecting isr to be available
another point is when any node goes down it takes a while to reassign the primary partitions and make kafka available, though config is there to set the time to trigger rebalancing, usually it kicks the rebalancing but the rebalancing itself takes lot of time
What problems are you solving with the product? What benefits have you realized?
streaming logs/stats from multiple devices and consumed by processing engine
Recommendations to others considering the product:
Its a great tool with high performance and millisecond level latency
Has got lot of debugging tools


    Varun K.

Review Kafka

  • April 30, 2020
  • Review provided by G2

What do you like best?
Low Latency , High Through put and replication
What do you dislike?
Apache Kafka does not support wildcard topic selection. Instead, it matches only the exact topic name. It is because selecting wildcard topics make it incapable to address certain use cases.
What problems are you solving with the product? What benefits have you realized?
Queue system for sms.
Recommendations to others considering the product:
For making progress async Kafka is good tool. In message queue, Kafka is popular in industry.


    Martin A.

Kafka stream processing at your finger tips

  • April 26, 2020
  • Review provided by G2

What do you like best?
We were looking for an open-source solution to perform stream processing. When our team found this, it was immediately accepted to be used as our permanent solution to achieve the goal we had.
What do you dislike?
We haven't found any issues so far in Kafka.
What problems are you solving with the product? What benefits have you realized?
This forum is not the right place to discuss problem statement solved with our clients
Recommendations to others considering the product:
Open-Source, Stable and Scalable platform to all your difficult problems. You don't have to search elsewhere when you have Kafka


    Swapnil G.

Kafka : A high capacity component

  • April 23, 2020
  • Review provided by G2

What do you like best?
High throughput, Multi-instance, Kafka Connect API
What do you dislike?
Confluent's version of Kafka because the UI is too bad.
What problems are you solving with the product? What benefits have you realized?
Performing Spark streaming using Apache Kafka Connect API.
Recommendations to others considering the product:
Use only HDP's version of Kafka. The confluent one is a bit messy.


    Information Technology and Services

I used apache kafka in our queuing engine for sending messages in microservices architecture.

  • April 23, 2020
  • Review provided by G2

What do you like best?
The best thing about apache kafka is its index maintainable structure.
What do you dislike?
I didn’t find any within my requirement.
Just that if I could get 247 support for best installation and runtime problems.
What problems are you solving with the product? What benefits have you realized?
Reducing all my cpu tasks to queue workers which makes my application lite.
Also many workers can use the same message which is best.


    Sahil M.

Kafka for ETL

  • April 22, 2020
  • Review provided by G2

What do you like best?
The way we can scale it, as opposed to rabbitmq, the persistent intermediate storage with ksql, and paralleling data by topics
What do you dislike?
The official sink and source connectors, from debezium have issues with some advanced data types, especially arrays and son, when reading from postgres WAL files.
What problems are you solving with the product? What benefits have you realized?
We did not use it for ETL, but are continuously using it as an advanced messaging broker for our microservices, with much detailed information available to us about data movement in the data bus, as it makes handling failure a lot easy
Recommendations to others considering the product:
Make sure first do a proper research for your use case, when implementing Kafka clusters, as it is an open-source software there might be things partially implemented and may not have support for specific requirements, a person in the team who can do some open-source contributions to manage the caveats would definitely help.