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Kafka

23.6K
22K
+ 1
607
Neon Database

17
12
+ 1
0
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Pros of Kafka
Pros of Neon Database
  • 126
    High-throughput
  • 119
    Distributed
  • 92
    Scalable
  • 86
    High-Performance
  • 66
    Durable
  • 38
    Publish-Subscribe
  • 19
    Simple-to-use
  • 18
    Open source
  • 12
    Written in Scala and java. Runs on JVM
  • 9
    Message broker + Streaming system
  • 4
    KSQL
  • 4
    Avro schema integration
  • 4
    Robust
  • 3
    Suport Multiple clients
  • 2
    Extremely good parallelism constructs
  • 2
    Partioned, replayable log
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Fun
  • 1
    Flexible
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    Cons of Kafka
    Cons of Neon Database
    • 32
      Non-Java clients are second-class citizens
    • 29
      Needs Zookeeper
    • 9
      Operational difficulties
    • 5
      Terrible Packaging
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      What is Kafka?

      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

      What is Neon Database?

      It is a fully managed serverless PostgreSQL. Neon separates storage and compute to offer modern developer features such as serverless, branching, bottomless storage, and more.

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      What companies use Kafka?
      What companies use Neon Database?
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      What tools integrate with Kafka?
      What tools integrate with Neon Database?

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      What are some alternatives to Kafka and Neon Database?
      ActiveMQ
      Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.
      RabbitMQ
      RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
      Amazon Kinesis
      Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
      Apache Spark
      Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
      Akka
      Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.
      See all alternatives