We know that when we host an application we initially need multiple servers, otherwise at the time of trafficking or we can say more clients requests, cannot handle the load and before AWS, the servers were very expensive, and it was very difficult to follow the budget pattern. Even before AWS the servers had a lot of security issues and the maintenance cost was high. So, AWS was launched to provide ease to the developer.
SO, WHAT IS AWS?
AWS stands for Amazon Web Services and was launched in 2006, and is a service platform that provides secure services based on the cloud, and it provides more than 200 fully featured services globally. And this process requires a set of actions from storing data to moving data through an automated process and businesses have an inordinate amount of data, so to analyze it and move to the final designation we need data pipelines.
So, to know about data pipelines in detail. Let us know about the true meaning of AWS data pipelines, its requirements, elements, strengths and weakness and much more.
What is AWS Data Pipeline?
AWS Data Pipeline provides a web service that helps users to automate the movement and transformation of data i.e., tasks can be fully dependent on previous tasks. With the help of AWS data pipeline user can examine the data which means user access where it is stored, transformation and scaling process and transfer the data quickly to AWS services like Amazon S3, Amazon RDS, Amazon DynamoDB does.
AWS Data Pipeline: NECESSITY
• Help with quick decision-making: AWS Data Pipeline helps businesses to easily extract and process large amounts of data which helps businesses to get insight updates, leverage and more trends that drive decision-making quickly.
• Helps in merge the data: Through the expansion of the cloud, there are multiple software that perform multiple functions and use different tools to store and analyze data, so data from each source is integrated into the final stage i.e., AWS Pipelines helps to get to aggregate and merge that insights.
• Flexible in trafficking: To add storage and processing capacity in minutes while trafficking, AWS Data Pipelines provide scalability to help process large volumes of data unlike legacy or traditional data pipelines that are rigid, slow, inaccurate and unable to scale.
• Easy access to information: AWS Data Pipelines helps businesses to automate the process of extracting data and moving it to analytics tools.
• Different Data Stores: In businesses, there are different types of data storage options like Amazon S3, Amazon Relational Database Service (RDS) and running database server on EC2 instances.
AWS Data Pipelines: ELEMENTS
• Support in full transformation: AWS Data Pipeline supports in full transformation with various activities like Hive Activity, Pig Activity, etc. And code-based change is supported with the ability to run user-supplied code in an EMR cluster or on on-premises clusters through Hadoop Activity.
• Flexible pricing mechanism: AWS Data Pipeline provides a flexible pricing feature in which the user pays only as per the time consumed.
• On-premises systems: AWS Data Pipeline allows the user to use on-premises systems for data sources or transformation and provides the facility to set up resources with the data pipeline.
• Simple interface: AWS Data Pipeline provides a simple interface that helps the user to set up complex tasks in just a few clicks.
• Process automation: AWS Data Pipeline automates the process between different sources, and it supports on-premise sources such as AWS as well as JDBC-based databases.
• Records operations: AWS Data Pipelines provides the user with the facility to record or schedule operations based on the success or failure of tasks.
AWS DATA PIPELINES: STRENGTHS AND WEAKNESS
• AWS Data Pipeline has the ability to acquire clusters and resources only when needed
• It provides fault-tolerant architecture that helps users with system stability and recovery.
• AWS Data Pipeline is easy to use control panel with pre-written templates for AWS databases.
• AWS Data Pipeline provides complete safety and security of data in motion or at rest and allows the control mechanism of AWS.
• AWS Data Pipeline is designed for AWS’s services and is not good at fetching data for third party services.
• AWS Data Pipeline is difficult for newbies, that is, the terms and logic are more complex than other tools like Airflow.
• When the user was working with pipelines, the resources were huge with multiple setups had to be maintained on compute resources.
In the above talk we discuss about AWS Data Pipeline which helps in automating the process and taking the data to the final stage and we also learn about the requirements, elements and strengths and weaknesses of AWS Data Pipelines.