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Amazon Kinesis vs Apache Storm: What are the differences?

Introduction In this article, we will discuss the key differences between Amazon Kinesis and Apache Storm, two popular streaming data processing platforms.

  1. Scalability: One major difference between Amazon Kinesis and Apache Storm lies in their scalability. Amazon Kinesis is a fully managed service offered by Amazon Web Services (AWS), which automatically scales based on the incoming data stream. It can handle large volumes of data without any additional configuration or management. On the other hand, Apache Storm requires manual configuration and management of resources for scaling. While it can scale to handle large workloads, the responsibility lies with the user to provision and manage the necessary resources.

  2. Ease of Use: Another difference is in the ease of use. Amazon Kinesis provides a simple and user-friendly interface, making it easier for developers to set up and manage data streams. It offers seamless integration with other AWS services, allowing developers to build end-to-end streaming applications easily. Apache Storm, on the other hand, has a steeper learning curve and requires more technical expertise to set up and operate. It does provide greater flexibility and control over the streaming process but can be more complex for beginners.

  3. Fault Tolerance: When it comes to fault tolerance, Amazon Kinesis provides built-in fault-tolerant capabilities. It automatically replicates data across multiple Availability Zones, ensuring high durability and availability. In case of failures, it can recover and resume processing without data loss. Apache Storm, on the other hand, relies on the user to implement fault tolerance mechanisms. It provides primitives for building fault-tolerant topologies, but the responsibility for ensuring fault tolerance lies with the user.

  4. Integration with Ecosystem: Amazon Kinesis is tightly integrated with the AWS ecosystem, allowing seamless integration with other AWS services like AWS Lambda, Amazon Redshift, or Amazon Elasticsearch. This integration enables developers to easily build scalable streaming architectures with various data processing capabilities. Apache Storm, on the other hand, can be integrated with a wide range of external tools and systems, providing more flexibility in the choice of technologies. It supports integration with databases, queues, and other data processing frameworks.

  5. Real-time vs. Near-Real-time: Amazon Kinesis is designed for real-time streaming data processing. It focuses on processing data in near real-time, typically with low latency. It provides capabilities like real-time analytics, real-time dashboards, and real-time processing of data. Apache Storm, on the other hand, is a distributed real-time computation system. It allows processing of streaming data with low latency but may not have the same level of real-time capabilities as Amazon Kinesis.

  6. Managed vs. Self-managed: Lastly, a significant difference is in the management aspect. Amazon Kinesis is a fully managed service, where Amazon takes care of the infrastructure, scaling, and maintenance. Users are only responsible for configuring and deploying their applications. In contrast, Apache Storm is a self-managed framework where users have to manage the infrastructure, scalability, and maintenance themselves. This gives users more control and flexibility but also requires more effort and resources.

In Summary, Amazon Kinesis is a fully managed, scalable, and user-friendly streaming data processing service tightly integrated with the AWS ecosystem, while Apache Storm is a self-managed, flexible, and powerful distributed real-time computation framework with greater control but higher complexity.

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Pros of Amazon Kinesis
Pros of Apache Storm
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    Scalable
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    Flexible
  • 6
    Easy setup
  • 4
    Event Processing
  • 3
    Clojure
  • 2
    Real Time

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Cons of Amazon Kinesis
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    What is 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.

    What is Apache Storm?

    Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

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    What companies use Amazon Kinesis?
    What companies use Apache Storm?
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    Jul 2 2019 at 9:34PM

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    What are some alternatives to Amazon Kinesis and Apache Storm?
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    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.
    Amazon SQS
    Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
    Amazon Kinesis Firehose
    Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.
    Firehose.io
    Firehose is both a Rack application and JavaScript library that makes building real-time web applications possible.
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