Best ways to stream data from different data sources to AWS S3.
Tags: aws, cloudnative, beginners, cloud
Published: 2022-12-21 19:08:22



## Introduction
Real-time data streaming from many sources to AWS S3 can be difficult, but it is also a potent method of ingesting and processing massive amounts of data for analytics, machine learning, and other use cases. We'll look at a few alternative methods for streaming data to S3 in this blog article and go through the advantages and disadvantages of each method.
An overview of how to stream data in real-time to AWS S3 from several data sources:

## Amazon Kinesis Data Streams

Kinesis Data Streams is a fully managed service that enables real-time, low-latency, high-throughput data streaming to S3. It is readily linked with other AWS services via Lambda or Kinesis Data Firehose, and it scales to handle millions of events per second.
If you require low latency and high throughput for real-time data streaming and you don't need to execute intricate data transformations, Kinesis Data Streams is a viable option. With Lambda or Kinesis Data Firehose, it is a fully managed service that scales to handle millions of events per second and is simply linked with other AWS services.

The simplicity and convenience of the use of Kinesis Data Streams are one of its key advantages, but if you need to do intricate data transformations, it might not be the ideal option.

## Amazon Managed Streaming for Apache Kafka (MSK)

Apache Kafka clusters in the cloud are simple to set up, run and grow thanks to Amazon Managed Streaming for Apache Kafka (MSK), a completely managed service. It offers a variety of features and tools to assist you in processing and transforming the data, and it can be used to stream data to S3 in real time.

MSK is a fantastic option if you want Apache Kafka's whole strength and flexibility for data streaming and processing, but it might not be as convenient or economical as some of the other alternatives.

## AWS Glue Streaming

AWS Glue Streaming is a feature of AWS Glue that allows you to process streaming data on the fly and store the results in a data store or data lake. It is built on top of Apache Spark and can be used to process data from a variety of sources, including Apache Kafka, Amazon Kinesis Data Streams, and Amazon Managed Streaming for Apache Kafka (MSK).

If you need to apply the rich set of APIs and connectors provided by utilizing Apache Spark, or if you need to do complex comparisons on the data, AWS Glue Streaming may be an excellent choice for processing and storing real-time data in S3.

AWS Glue Streaming can be a better option if you need to execute more intricate data transformations or if you want to fully utilize Apache Spark for data processing. It is less suited to high-throughput, low-latency applications than Kinesis Data Streams, however, and it requires more setup, upkeep, and modification than some of the other real-time records streaming options offered by using AWS, such as Kinesis Data Streams and Lambda.

## Conclusion

In conclusion, your particular needs and requirements will determine the optimum method for real-time data streaming to S3 from various data sources. Kinesis Data Streams is a suitable option if you require low latency and high throughput as well as don’t need to do complicated data transformations. AWS Glue Streaming or MSK may be preferable if you need to do intricate data transformations or if you want to fully utilize Apache Spark for data processing. The best option will ultimately depend on your particular use case and the compromises you are prepared to make between complexity, performance, and cost.


If you need to apply the rich set of APIs and connectors provided by utilizing Apache Spark, or if you need to do complex comparisons on the data, AWS Glue Streaming may be an excellent choice for processing and storing real-time data in S3.