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Learn MorePros of AWS Data Pipeline
Pros of AWS Step Functions
Pros of Dyn
Pros of AWS Data Pipeline
- Easy to create DAG and execute it1
Pros of AWS Step Functions
- Integration with other services7
- Easily Accessible via AWS Console5
- Complex workflows5
- Pricing5
- Scalability3
- Workflow Processing3
- High Availability3
Pros of Dyn
- API6
- Managed DNS5
- Web interface5
- Security4
- Customer Service Access3
- Fast1
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What is AWS Data Pipeline?
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.
What is AWS Step Functions?
AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
What is Dyn?
An all-in-one Managed DNS service for your registered domain names. Dyn DNS is the perfect solution for your domain name’s DNS needs, whether it is for personal or business use. It gives you complete control over your DNS zone and its associated DNS records, complete with a simple DNS management web interface.
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What companies use Dyn?
What companies use AWS Data Pipeline?
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What tools integrate with AWS Data Pipeline?
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What tools integrate with Dyn?
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What are some alternatives to AWS Data Pipeline, AWS Step Functions, and Dyn?
AWS Glue
A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
Apache NiFi
An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
AWS Batch
It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.
Azure Data Factory
It is a service designed to allow developers to integrate disparate data sources. It is a platform somewhat like SSIS in the cloud to manage the data you have both on-prem and in the cloud.