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Advice on AWS Data Pipeline and Azure Pipelines
Balaramesh Thiyagaraj
We are currently using Azure Pipelines for continous integration. Our applications are developed witn .NET framework. But when we look at the online Jenkins is the most widely used tool for continous integration. Can you please give me the advice which one is best to use for my case Azure pipeline or jenkins.
Replies (1)
shailesh shah
If your source code is on GitHub, also take a look at Github actions. https://github.com/features/actions
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Learn MorePros of AWS Data Pipeline
Pros of Azure Pipelines
Pros of AWS Data Pipeline
- Easy to create DAG and execute it1
Pros of Azure Pipelines
- Easy to get started4
- Unlimited CI/CD minutes3
- Built by Microsoft3
- Yaml support2
- Docker support2
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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 Azure Pipelines?
Fast builds with parallel jobs and test execution. Use container jobs to create consistent and reliable builds with the exact tools you need. Create new containers with ease and push them to any registry.
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What are some alternatives to AWS Data Pipeline and Azure Pipelines?
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.
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.
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.