Amazon Kinesis vs Amazon SQS: What are the differences?

Introduction

1. Data Volume and Throughput:

Amazon Kinesis is designed for handling massive streams of data with high throughput, allowing real-time processing of large amounts of data. On the other hand, Amazon SQS is best suited for decoupling application components and for smaller message volumes.

2. Data Retention:

In Amazon Kinesis, data retention is based on the time-to-live (TTL) setting, allowing data to be stored for a specified period. Conversely, Amazon SQS retains messages for a maximum of 14 days, after which they are automatically deleted.

3. Data Processing Model:

Amazon Kinesis offers real-time data streaming capabilities for processing continuously flowing data, whereas Amazon SQS follows a traditional message-queuing model, ensuring reliable message delivery between distributed components.

4. Scalability:

Amazon Kinesis provides dynamic scaling capabilities to handle fluctuating workloads efficiently, while Amazon SQS offers horizontal scaling by allowing multiple message queues and concurrent consumers to manage increased message processing.

5. Ordering of Messages:

Amazon Kinesis maintains the order of records within a shard, ensuring chronological processing of data within a partitioned stream. In contrast, Amazon SQS does not guarantee the ordering of messages across multiple queues, prioritizing fast and reliable message delivery.

6. Fan-Out Capability:

Amazon Kinesis supports fan-out architecture, allowing parallel processing of data streams by multiple consumers without impacting the performance. This feature is not available in Amazon SQS, where each message is processed by a single consumer exclusively.

In Summary, Amazon Kinesis and Amazon SQS differ in their handling of data volume, retention policies, data processing models, scalability options, message ordering, and fan-out capabilities.