Amazon Kinesis vs Amazon Kinesis Firehose: What are the differences?

Introduction

Amazon Kinesis and Amazon Kinesis Firehose are both services offered by Amazon Web Services (AWS) for real-time streaming of data.

1. Flexibility of Data Streaming vs End-to-End Processing:

• Amazon Kinesis: It offers both real-time streaming and storage capabilities, allowing users to ingest, process, and analyze streaming data from various sources.
• Amazon Kinesis Firehose: It is focused on data ingestion and is designed to load streaming data directly into data stores like Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service in near real-time without requiring any additional processing.

2. Ease of Use and Simplified Management:

• Amazon Kinesis: It provides more control over data processing and offers features like data retention, scaling, and detailed monitoring for managing streaming data effectively.
• Amazon Kinesis Firehose: It simplifies the data ingestion process by automatically handling data buffering, compressing, encrypting, and delivering the data to the desired storage service, reducing the need for managing infrastructure or data processing tasks.

3. Integration with Other AWS Services:

• Amazon Kinesis: It can integrate with various AWS services like AWS Lambda, Amazon Redshift, Amazon EMR, and Amazon Elasticsearch Service, allowing advanced data processing and analytics.
• Amazon Kinesis Firehose: It directly integrates with services like Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service, making it easier to load streaming data into these services without additional integration efforts.

4. Data Transformation and Enrichment:

• Amazon Kinesis: It provides the ability to write custom code using the Kinesis Client Library (KCL) for processing and transforming streaming data before storing or analyzing it.
• Amazon Kinesis Firehose: It has limited data transformation capabilities and usually requires external services like AWS Lambda for performing transformations on the data before delivering it to the storage service.

5. Processing Durability:

• Amazon Kinesis: It stores streaming data for a configurable retention period, providing durability and the ability to replay the data multiple times if needed.
• Amazon Kinesis Firehose: It doesn't retain the data for a longer duration as its main purpose is to efficiently deliver the data to the storage service, making it less suitable for scenarios requiring long-term data retention.

6. Pricing Structure:

• Amazon Kinesis: It has a pay-as-you-go pricing model based on the number of shards and data processing capacity required.
• Amazon Kinesis Firehose: It has a simple pricing structure based on the amount of data ingested and any additional optional data transformation operations.

In summary, Amazon Kinesis provides more flexibility for processing and analyzing streaming data, while Amazon Kinesis Firehose simplifies the data ingestion process and seamlessly integrates with storage services.