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Amazon Kinesis vs AWS Data Pipeline: What are the differences?
Developers describe Amazon Kinesis as "Store and process terabytes of data each hour from hundreds of thousands of sources". 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. On the other hand, AWS Data Pipeline is detailed as "Process and move data between different AWS compute and storage services". AWS Data Pipeline is a web service that provides a simple management system for data-driven workflows. Using AWS Data Pipeline, you define a pipeline composed of the “data sources” that contain your data, the “activities” or business logic such as EMR jobs or SQL queries, and the “schedule” on which your business logic executes. For example, you could define a job that, every hour, runs an Amazon Elastic MapReduce (Amazon EMR)–based analysis on that hour’s Amazon Simple Storage Service (Amazon S3) log data, loads the results into a relational database for future lookup, and then automatically sends you a daily summary email.
Amazon Kinesis can be classified as a tool in the "Real-time Data Processing" category, while AWS Data Pipeline is grouped under "Data Transfer".
Some of the features offered by Amazon Kinesis are:
- Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report.
- Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.
- High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs.
On the other hand, AWS Data Pipeline provides the following key features:
- You can find (and use) a variety of popular AWS Data Pipeline tasks in the AWS Management Console’s template section.
- Hourly analysis of Amazon S3‐based log data
- Daily replication of AmazonDynamoDB data to Amazon S3
Pros of Amazon Kinesis
- Scalable9
Pros of AWS Data Pipeline
- Easy to create DAG and execute it1
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Cons of Amazon Kinesis
- Cost3