Amazon Kinesis

Amazon Kinesis

Amazon Kinesis is a managed service that allows for real-time streaming data ingestion and processing. It can ingest data streams from multiple sources, process the data, and route the results to various endpoints.
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realtime ingestion processing

Amazon Kinesis: Real-Time Data Ingestion & Processing Service

A managed service allowing real-time streaming data ingestion, processing, and routing to multiple endpoints from diverse sources.

What is Amazon Kinesis?

Amazon Kinesis is a cloud-based managed service offered by Amazon Web Services (AWS) to allow for real-time streaming data ingestion and processing. It is designed to easily ingest and process high volumes of streaming data from multiple sources simultaneously, making it well-suited for real-time analytics and big data workloads.

Some key capabilities and benefits of Amazon Kinesis include:

  • Scalable data streams that can ingest gigabytes of data per second from hundreds of thousands of sources
  • Real-time processing of streaming data as soon as it arrives to enable near-instant analytics and insights
  • Customizable data processing through Kinesis Data Analytics and other AWS analytics services
  • Easy integration with a variety of data sources like web/mobile apps, IoT devices, and more through Kinesis agents and producers
  • Durable storage of streaming data for later replay and reprocessing needs
  • High availability and durability built in to handle data streams 24/7

Amazon Kinesis integrates closely with other AWS services like S3, Redshift, and Lambda to provide a complete platform for streaming data intake, processing, analysis, and storage. The service handles the underlying infrastructure to simplify real-time analytics at any scale.

Amazon Kinesis Features

Features

  1. Real-time data streaming
  2. Scalable data ingestion
  3. Data processing through Kinesis Data Analytics
  4. Integration with other AWS services
  5. Serverless management
  6. Data replay capability

Pricing

  • Pay-As-You-Go

Pros

Handles massive streams of data in real-time

Fully managed service, no servers to provision

Automatic scaling to match data flow

Integrates nicely with other AWS services

Replay capability enables reprocessing of data

Cons

Can get expensive with high data volumes

Complex to set up and manage

Limits on maximum stream size and shard throughput

No automatic data retention policies


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