Apache Airflow vs. SnapLogic

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

Snaplogic is unique from other IPASS tools if you're very sensitive about data security as they have an on-premise option where your data never needs to leave your data center. And data pipelines can be quickly created if Snaplogic has the requisite connector to your data sources. On the downside, if you're transforming a large amount of data for example in training machine learning models, a tool with elastic compute capability is more appropriate.

• In charge of the ETL processes.
• As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.

Incentivized

• Easy access to any type of source system. Data could be in any format.
• Very beautiful visual representation of transforms that makes it super easy to use it by any non developer.
• It can be run in cloud or on-premise. helping you choose your comfort of security.
• Has pretty good customer support and have recently started their community forum as well.

Incentivized

• they should bring in some time based scheduling too not only event based
• they do not store the metadata due to which we are not able to analyze the workflows
• they only support python as of now for scripted pipeline writing

Incentivized

• They need to have a way to connect to GitHub to allow the users to maintain their version control in GitHub. This is a missing functionality.
• As pipelines become complex, it's difficult to have all the snaps stitched together - just like to see it done differently.
• They do not have a way to start/stop a preview. This is hard to use, especially if you have to stop an accidental preview invocation.

Incentivized

This has been hands down the BEST software company I have ever used and dealt with. I am a 25 year IT veteran at this college. They go above and beyond in soliciting our feedback/input and proactively follow up about bugs, issues, etc. I have given multiple potential clients my thoughts and after seeing the SL demo they all sign up. I appreciate their support model, it's REFRESHING!

Incentivized

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

It is very powerful but has a steep learning curve

Incentivized

They can be prompt but they have not been as useful as I've wanted. We had a bug that affected many of our customers through an API connection between SnapLogic and our platform. Eventually they were able to figure it out, but it took a long time of negotiating between our engineering team and theirs. Additionally, we installed the SnapLogic groundplex for our customers and we've run into a bunch of problems of connectivity. If SnapLogic offered to be on those calls with our clients to troubleshoot how to fix these problems, I would give them a better grade here.

Incentivized

The groundplex in our VPC is very nice for security reasons and the SnapLogic team was extremely helpful during our implementation

Incentivized

There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.

Incentivized

We opted for SnapLogic due its ease of use and the flexibility it offers, it was the platform that was strongest in both application integration and data integration and both were use cases we wanted to be able to cover.

• A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
• Allowed us to implement complex data pipelines easily and at a relatively low cost

Incentivized

• We have cut development time down by at least 70%
• The software was more on the expensive side at renewal which required some further approvals to be sought for the spend
• More developers are able to build and use Snaplogic pipelines in their projects

Incentivized