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Amazon Kinesis

637
505
+ 1
11
Apache Storm

178
252
+ 1
24
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Pros of Amazon Kinesis
Pros of Apache Storm
  • 7
    Scalable
  • 4
    Cons
  • 10
    Flexible
  • 6
    Easy setup
  • 3
    Clojure
  • 3
    Event Processing
  • 2
    Real Time

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Cons of Amazon Kinesis
Cons of Apache Storm
  • 2
    Cost
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    - No public GitHub repository available -

    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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    What tools integrate with Amazon Kinesis?
    What tools integrate with Apache Storm?

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    Blog Posts

    Jul 2 2019 at 9:34PM

    Segment

    Google AnalyticsAmazon S3New Relic+25
    10
    5885
    GitHubPythonNode.js+47
    50
    69438
    GitHubDockerAmazon EC2+23
    12
    6360
    GitHubSlackMySQL+44
    109
    49985
    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.
    See all alternatives