Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL.
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Jitterbit
Score 7.0 out of 10
N/A
Jitterbit is a cloud integration technology for cloud, social or mobile apps. It provides accessibility for
non-technical users, including easily creating API’s and data transformation scripts within the
integrations.
$1,000
per month
Zapier
Score 8.8 out of 10
N/A
The Zapier Automation Platform designed to integrate data between web apps. It is scaled for small to mid-sized businesses, with a functional but limited free version of the program.
I'd consider Zapier a "pro-sumer" solution. It's not as powerful as more expensive solutions out there. But it's definitely for the business minded user.
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.
This is a great tool for bringing data out of your locked, internal systems and getting it into the cloud. It meshes well with Salesforce and is fairly easy to use, helping the transition from other older, more complex tools into a more modern environment. It has lots of competition in this space and some are better than others, but if your data is straight forward and you know it well, Jitterbit will get the job done. If you are not as close or comfortable with your data and need to do some wildly complex migrations, there might be better packages out there for you.
If you have processes that are now managed and controlled using a spreadsheet, Zapier will give you a lot more control over what is happening and will help you increase productivity by eliminating simple steps such as sending emails and sharing information with your colleagues. It frees time for very transactional activities.
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.
Ease of use - multiple people in the organization can set up and run Zaps per their specific use cases without much training.
Connectivity - Zapier is able to connect to multiple applications we use on a regular basis.
Functionality - Zapier provides embedded functionality within the app itself (email, data conversion), but also appropriate triggers and actions for apps it connects to.
Versatile - Zapier can execute complicated and simple tasks and thus has many use cases.
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.
Migrating operations from QA to Production work well for initial deployment, however, when migrating an update to an existing job to production, sometimes certain project items are duplicated. This is not the end of the world... the duplicates can be removed, but would be nice if it was not required.
I have not found a way to trap under-the-covers SOAP errors (for example, when a query you are running against Salesforce takes too long). You get a warning error in the operation log that the job only pulled a "partial" file, but it does not fail.
I have been evaluating other tools as a continuous improvement practice. I would like something that would be easier to use for a non-technical user. I work for a small organization and have no back-up for Jitterbit if something happens to me. We don't have the technically savvy employees to understand it.
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.
The interface is very user-friendly, and there are also many tools to help a brand-new user get started. For example, you can put your Zap idea into the AI bot, and it will basically build a shell of your Zap to get started on. The format for each step within a Zap is also very helpful (set up the connection/app, set up the fields/details, then test).
Before we purchased Zapier, I contacted support and asked them if Zapier could support my intended workflow (this is actually a selection on their support form - awesome). Within 2 hours, I was contacted by a support team member who seemed sure it would work, but granted me premium access for 2 weeks to try it out for myself. Sure enough, it did! Ever since then, support has replied rapidly to any problems I have experienced and answered my questions within a few sentences.
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.
Evaluated Dell Boomi and Celigo as alternatives prior to purchasing Jitterbit. We went with Jitterbit at that time because we could handle all changes ourselves without any assistance from Jitterbit, and we liked their size and nimbleness. Dell Boomi was too big for us, and Celigo at that time did not have a self-service model. Every change had to go through them (although that has since changed). We were not in a position to be able to wait for someone to make changes for us given the rate of change within the business.
We actually utilize both Integromat and Zapier at our company, for all the reasons detailed in this review. Though Zapier is excellent for simple client integrations, we often run into internal use cases that require complexity that Zapier cannot provide. Specifically working with API calls (not just webhooks), complex multi-step integrations with Routing/parsing/etc, and large volume integrations. Integromat is perfect for these use cases, but doesn’t provide the simplicity and account scalability that Zapier offers.
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
The time it takes to connect systems has reduced by orders of magnitude. Previously, we would custom-develop connectors between various systems and they would all be managed by different vendors. With Jitterbit speed-to-deploy and the efficiency gained by managing all connections in one dashboard has been the greatest piece of the ROI.
