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Amazon Kinesis Firehose

Simple and Scalable Data Ingestion
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What is 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.
Amazon Kinesis Firehose is a tool in the Real-time Data Processing category of a tech stack.

Who uses Amazon Kinesis Firehose?

Companies
88 companies reportedly use Amazon Kinesis Firehose in their tech stacks, including CRED, Shelf, and Primer.

Developers
95 developers on StackShare have stated that they use Amazon Kinesis Firehose.

Amazon Kinesis Firehose Integrations

Amazon S3, Amazon Redshift, LocalStack, Dashbird, and Foxpass are some of the popular tools that integrate with Amazon Kinesis Firehose. Here's a list of all 5 tools that integrate with Amazon Kinesis Firehose.
Decisions about Amazon Kinesis Firehose

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon Kinesis Firehose in their tech stack.

Praveen Mooli
Engineering Manager at Taylor and Francis · | 14 upvotes · 1.8M views

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

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Amazon Kinesis Firehose's Features

  • Easy-to-Use
  • Integrated with AWS Data Stores
  • Automatic Elasticity
  • Near Real-time

Amazon Kinesis Firehose Alternatives & Comparisons

What are some alternatives to Amazon Kinesis Firehose?
Stream
Stream allows you to build scalable feeds, activity streams, and chat. Stream’s simple, yet powerful API’s and SDKs are used by some of the largest and most popular applications for feeds and chat. SDKs available for most popular languages.
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.
Google Cloud Dataflow
Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Amazon Kinesis Firehose's Followers
146 developers follow Amazon Kinesis Firehose to keep up with related blogs and decisions.