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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cloud Storage
  5. Airflow vs Azure Storage

Airflow vs Azure Storage

OverviewDecisionsComparisonAlternatives

Overview

Azure Storage
Azure Storage
Stacks1.3K
Followers787
Votes52
Airflow
Airflow
Stacks1.7K
Followers2.8K
Votes128

Airflow vs Azure Storage: What are the differences?

Developers describe Airflow as "A platform to programmaticaly author, schedule and monitor data pipelines, by Airbnb". 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. On the other hand, Azure Storage is detailed as "Reliable, economical cloud storage for data big and small". Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

Airflow belongs to "Workflow Manager" category of the tech stack, while Azure Storage can be primarily classified under "Cloud Storage".

Some of the features offered by Airflow are:

  • Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writting code that instantiate pipelines dynamically.
  • Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.
  • Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built in the core of Airflow using powerful Jinja templating engine.

On the other hand, Azure Storage provides the following key features:

  • Blobs, Tables, Queues, and Files
  • Highly scalable
  • Durable & highly available

Airflow is an open source tool with 12.7K GitHub stars and 4.62K GitHub forks. Here's a link to Airflow's open source repository on GitHub.

Starbucks, Yammer, and Microsoft are some of the popular companies that use Azure Storage, whereas Airflow is used by Slack, Repro, and WePay. Azure Storage has a broader approval, being mentioned in 82 company stacks & 42 developers stacks; compared to Airflow, which is listed in 70 company stacks and 30 developer stacks.

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Advice on Azure Storage, Airflow

Anonymous
Anonymous

Jan 19, 2020

Needs advice

I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.

294k views294k
Comments

Detailed Comparison

Azure Storage
Azure Storage
Airflow
Airflow

Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

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.

Blobs, Tables, Queues, and Files;Highly scalable;Durable & highly available;Premium Storage;Designed for developers
Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writting code that instantiate pipelines dynamically.;Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.;Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built in the core of Airflow using powerful Jinja templating engine.;Scalable: Airflow has a modular architecture and uses a message queue to talk to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Statistics
Stacks
1.3K
Stacks
1.7K
Followers
787
Followers
2.8K
Votes
52
Votes
128
Pros & Cons
Pros
  • 24
    All-in-one storage solution
  • 15
    Pay only for data used regardless of disk size
  • 9
    Shared drive mapping
  • 2
    Cheapest hot and cloud storage
  • 2
    Cost-effective
Cons
  • 2
    Direct support is not provided by Azure storage
Pros
  • 53
    Features
  • 14
    Task Dependency Management
  • 12
    Cluster of workers
  • 12
    Beautiful UI
  • 10
    Extensibility
Cons
  • 2
    Observability is not great when the DAGs exceed 250
  • 2
    Open source - provides minimum or no support
  • 2
    Running it on kubernetes cluster relatively complex
  • 1
    Logical separation of DAGs is not straight forward
Integrations
Microsoft Azure
Microsoft Azure
No integrations available

What are some alternatives to Azure Storage, Airflow?

Amazon S3

Amazon S3

Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web

Amazon EBS

Amazon EBS

Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage.

Google Cloud Storage

Google Cloud Storage

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

Minio

Minio

Minio is an object storage server compatible with Amazon S3 and licensed under Apache 2.0 License

OpenEBS

OpenEBS

OpenEBS allows you to treat your persistent workload containers, such as DBs on containers, just like other containers. OpenEBS itself is deployed as just another container on your host.

GitHub Actions

GitHub Actions

It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

Rackspace Cloud Files

Rackspace Cloud Files

Cloud Files, powered by OpenStack®, provides an easy to use online storage for files and media which can be delivered globally at blazing speeds over Akamai's content delivery network (CDN).

Storj

Storj

It is an open source, decentralized file storage solution. It uses encryption, file sharing, and a blockchain-based hash table to store files on a peer-to-peer network. The goal is to make cloud file storage faster, cheaper, and private.

Apache Beam

Apache Beam

It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.

RunAbove

RunAbove

We give you full access to the OpenStack API, which our compute (Nova) and storage (Swift) solutions are based on. This means no provider lock-in and easy automation of all your deployments. You can also manage your account and billing details via our RESTful API. You can choose between Horizon or OVH's easy-to-use web panel.

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