Aws Data pipeline
AWS Data Pipeline is a web service that allows you to process and transport data between AWS computing and storage services, as well as on-premises data sources, at predetermined intervals. Data that was previously locked up in on-premises data silos may also be moved and processed using AWS Data Pipeline.
AWS Data Pipeline is a web service that allows customers to create automated data transfer and transformation operations. To put it another way, it provides data extraction, loading, and transformation as a service. To use their data, users don't need to build a complicated ETL or ELT platform; instead, they may use Amazon's preset settings and templates. The Data pipeline uses processing power other than the source and destination databases for the majority of its operations, and this capacity comes from Amazon's computing services like EMR.
AWS Data Pipeline – Features
- As previously stated, the AWS Data pipeline enables the automation of operations between various sources and objectives. It works with the majority of AWS sources as well as traditional on-premise sources like JDBC databases.
- Users can plan or chain these activities based on the success or failure of upstream tasks using a data pipeline.
- Various service activities, such as HiveActivity, PigActivity, and SQLActivity, provide extensive transformation processes. HadoopActivity, with its ability to run user-supplied code on an EMR cluster or on-premise cluster, supports a custom code-based transformation.
- Customers may utilise the EMR activity to establish an EMR cluster only when needed, and then perform their processing or transformation operations using a HadoopActivity.
- Customers can utilise their on-premise system for data sources or transformations as long as the computing resources are configured with data pipeline task runners.
- It has a fairly flexible price model, with the customer just paying for the time the computing resources are used, as well as a set cost for recurring activities.
