Apache Storm vs AWS Lambda

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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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Why do developers choose Apache Storm?
Why do developers choose AWS Lambda?

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    What tools integrate with Apache Storm?
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      What are some alternatives to Apache Storm and AWS Lambda?
      Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
      AWS Elastic Beanstalk
      Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
      Azure Functions
      Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.
      AWS Step Functions
      AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
      Google App Engine
      Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
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      Decisions about Apache Storm and AWS Lambda
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      Reviews of Apache Storm and AWS Lambda
      Review ofAWS LambdaAWS Lambda

      I switched my auto chatbot to run in lambda and it was peace !

      How developers use Apache Storm and AWS Lambda
      Avatar of Nathan Heffley
      Nathan Heffley uses AWS LambdaAWS Lambda

      To use Pusher's presence channel each client must be connected through a backend authentication system. While Pointer doesn't actually have any login based authentication it still needed a backend system to connect users to the proper channel.

      A small function was built that only gets called when a user first joins a session. After the user is authenticated they can communicate directly with other clients on the same channel. This made the authentication code the perfect candidate for a serverless function. Using AWS Lambda through Netlify's Functions feature made it a breeze to host.

      Avatar of Pinterest
      Pinterest uses Apache StormApache Storm

      In addition to batch processing, we also wanted to achieve real-time data processing. For example, to improve the success rate of experiments, we needed to figure out experiment group allocations in real-time once the experiment configuration was pushed out to production. We used Storm to tail Kafka and compute aggregated metrics in real-time to provide crucial stats.

      Avatar of Simple Merchant
      Simple Merchant uses AWS LambdaAWS Lambda

      We're moving almost the entirety of our backend processes into Lambda. This has given us vast cost savings in terms of pure infrastructure billing - and time worrying about platform and scale. This move has also made our architecture almost entirely event-driven - another huge benefit as our business itself is inherently event-driven.

      Avatar of Volkan Özçelik
      Volkan Özçelik uses AWS LambdaAWS Lambda

      I mostly use AWS Lambda for triggering DevOps-related actions, like triggering an alarm or a deployment, or scheduling a backup.

      I haven’t gone totally “serverless” and I’m not planning to go 100% serverless anytime soon.

      But when I do, AWS Lambda will be an important element in my serverless setup.

      Avatar of Promethean TV
      Promethean TV uses AWS LambdaAWS Lambda

      PrometheanTV uses various Lambda functions to provide back-end capabilities to the platform without the need of deploying servers. Examples include, geo lookup services, and data aggregation services.

      Avatar of Yelp
      Yelp uses Apache StormApache Storm

      Real-time analytics are much better than periodically run batch jobs, so recently we open sourced Pyleus which allows anyone to write Storm topologies using Python.

      Avatar of Flux Work
      Flux Work uses AWS LambdaAWS Lambda

      Serverless is the future. And AWS Lambda is the most mature FaaS out there. AWS SAM makes it easy to package Lambda as micro-apps.

      Avatar of Blue Kangaroo
      Blue Kangaroo uses Apache StormApache Storm

      Real-time log processing for user profiling

      Avatar of JimmyCode
      JimmyCode uses Apache StormApache Storm

      Batch processing and as recommendation tool.

      Avatar of brenoinojosa
      brenoinojosa uses Apache StormApache Storm

      Tasks in parallel are run by Storm.

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