Amazon Elastic Block Store (EBS) vs. Apache Airflow

It provides the optimized storage performance and cost for your workload and these options really work with SSD-backed storage and it improves the database performance. Keeping backups of your EC2 resources, including EBS volumes is a little bit tricky and its takes some more time and increase through put is also a tiring job to do.

Incentivized

Airflow is well-suited for data engineering pipelines, creating scheduled workflows, and working with various data sources. You can implement almost any kind of DAG for any use case using the different operators or enforce your operator using the Python operator with ease. The MLOps feature of Airflow can be enhanced to match MLFlow-like features, making Airflow the go-to solution for all workloads, from data science to data engineering.

Incentivized

• Raw storage capacity attached to your instance operative system
• Frequent data rewriting (mission critical for reporting)
• Low latency connectivity (14 reporting subsidiaries in different time zones)
• Videly spreaded for implementation
• Fast accessible drive
• Block storage are core for Java, Net mobile applications

Incentivized

• Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
• Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
• Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.

Incentivized

• Creating too much EBS can be disaster if you are not properly organized by tags
• In terms of pricing it's a bit on higher side.
• In terms of performance, there is room for improvement as sometimes reading or saving the data can be painful.

Incentivized

• UI/Dashboard can be updated to be customisable, and jobs summary in groups of errors/failures/success, instead of each job, so that a summary of errors can be used as a starting point for reviewing them.
• Navigation - It's a bit dated. Could do with more modern web navigation UX. i.e. sidebars navigation instead of browser back/forward.
• Again core functional reorg in terms of UX. Navigation can be improved for core functions as well, instead of discovery.

Incentivized

Amazon EBS is a great tool and fairly easy to use as long as you are familiar with the Amazon Web Service ecosystem. It allows a great way for you to move storage around easily and allows you to quickly provision storage as needed based on the business requirement. For us, it's easy to move between our EC2 images that had been linked with EBS storage between these Amazon accounts.

For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.

Incentivized

The support for Amazon Elastic Block Store is great as long as you can articulate your needs. Like most tools, there may be some back and forth before you find a support person that is knowledgable in the tool and can provide you with necessary insights.

So far I have only used Amazon Elastic Block Store (EBS) and Azure but comparatively [I] prefer AWS elastic Block store as its having more advantages than Azure and I found it quite satisfactory and it helped a lot for information storage. We are not looking for any other hosting provider at this time.

Incentivized

Multiple DAGs can be orchestrated simultaneously at varying times, and runs can be reproduced or replicated with relative ease. Overall, utilizing Apache Airflow is easier to use than other solutions now on the market. It is simple to integrate in Apache Airflow, and the workflow can be monitored and scheduling can be done quickly using Apache Airflow. We advocate using this tool for automating the data pipeline or process.

Incentivized

• When your application needs high IOPS storage, this is a great solution that will keep your business functioning.
• Without Amazon Elastic Block Store you could try spreading your data across several standard drives, but that introduces complexity and still has IOPS limits.

Incentivized

• Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
• Donot use it if you have very less usecases

Incentivized