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Apache Storm

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Apache Storm vs AWS Lambda: What are the differences?

Apache Storm: Distributed and fault-tolerant realtime computation. 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; AWS Lambda: Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB. AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Apache Storm can be classified as a tool in the "Stream Processing" category, while AWS Lambda is grouped under "Serverless / Task Processing".

Some of the features offered by Apache Storm are:

  • Storm integrates with the queueing and database technologies you already use
  • Simple API
  • Scalable

On the other hand, AWS Lambda provides the following key features:

  • Extend other AWS services with custom logic
  • Build custom back-end services
  • Completely Automated Administration

"Flexible" is the primary reason why developers consider Apache Storm over the competitors, whereas "No infrastructure" was stated as the key factor in picking AWS Lambda.

Apache Storm is an open source tool with 6.23K GitHub stars and 4.07K GitHub forks. Here's a link to Apache Storm's open source repository on GitHub.

Udemy, Delivery Hero SE, and Nubank are some of the popular companies that use AWS Lambda, whereas Apache Storm is used by Spotify, Twitter, and trivago. AWS Lambda has a broader approval, being mentioned in 2175 company stacks & 12275 developers stacks; compared to Apache Storm, which is listed in 57 company stacks and 110 developer stacks.

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Pros of Apache Storm
Pros of AWS Lambda
  • 10
    Flexible
  • 6
    Easy setup
  • 3
    Clojure
  • 3
    Event Processing
  • 2
    Real Time
  • 127
    No infrastructure
  • 82
    Cheap
  • 69
    Quick
  • 57
    Stateless
  • 47
    No deploy, no server, great sleep
  • 9
    AWS Lambda went down taking many sites with it
  • 6
    Event Driven Governance
  • 5
    Auto scale and cost effective
  • 5
    Extensive API
  • 5
    Easy to deploy
  • 4
    VPC Support
  • 2
    Integrated with various AWS services

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Cons of Apache Storm
Cons of AWS Lambda
    Be the first to leave a con
    • 5
      Cant execute ruby or go
    • 0
      Can't execute PHP w/o significant effort

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    - No public GitHub repository available -

    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.

    What is AWS Lambda?

    AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

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    What companies use Apache Storm?
    What companies use AWS Lambda?
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    What tools integrate with Apache Storm?
    What tools integrate with AWS Lambda?

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    What are some alternatives to Apache Storm and AWS Lambda?
    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.
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    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 Flume
    It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.
    Apache Flink
    Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
    See all alternatives