Azure Data Factory vs. Dataloader.io

In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.

Incentivized

Dataloader is an incredible asset for a large organization or an organization that has a robust Salesforce environment. Specifically, Dataloader has allowed our sales team to focus on driving sales while our operations team can load the data they need in a manner that allows for robust reporting and tracking on our sales process. Organizations with less robust Salesforce environments or Salesforce environments in which many people are expected to maintain their own information likely do not need Dataloader.

Incentivized

• Creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code.
• Hybrid data integration is easily and agilely possible through this software.
• It has lot of various useful components

Incentivized

• The selection of objects is much better and more extensive than the Salesforce built in data loader.
• Cross referencing of fields for record IDs is easy to use. I can work through this so much more quickly than using the built in Salesforce data loader.
• Success and error files are easy to identify what needs to be fixed (errors) and identification of records created (successes), so you can quickly do spot checks in your Salesforce org after doing a data load.
• The number of rows per month for a basic package, 100,000, is great for our business.

Incentivized

• Learning curve for pipeline creation interface.
• Alerting isn't necessarily built in. Had to work around this to meet team needs.
• With GIT enabled, some features can only be done via git, while some need to be done via the portal.

Incentivized

• At the moment, I can't find a way to rename jobs. This would be useful to organize what was previously created hastily by techs in a rush.
• A preview of the job, especially upserts, would take a great deal of stress away from some of us (especially those who are not so confident in their ETL practice).
• A native vlookup equivalent may be a welcome addition.

It is easy to use and doesn't require a security token, so I enjoy using it. It also doesn't require any download or installation, which is sometimes a blocker to gettingthings done if the company has limits. also, the dataloader.io is easy for other people to pick up, so others can have visibility into the data jobs that have occurred

So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Incentivized

It is an intuitive application to use. Within a few clicks, you can be signed in to your org and ready to perform tasks. Data imports/exports/updates are streamlined so you can quickly start and configure your jobs. These can run in the background while you set up new tasks. Job history and tasks currently running on are on your home screen.

Incentivized

Dataloader is made for updating, inserting, and deleting of contacts. For these operations this tool is excellent.

Incentivized

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

Incentivized

Customer support might be where Dataloader.io saves money. Most of the competitors offer 24/7 live support but Dataloader.io only offers support via email and the community. Those types of support work fine until you need an answer right away. Some questions can't wait until the next business day or business hours for a reply.

Incentivized

Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a visual interface for designing ETL workflows, but our team found Azure Data Factory's interface more intuitive.

Incentivized

The UI of Dataloader.IO is far more advanced, user-friendly, and current, than any of the options above. The ability to several tasks (Imports/Exports) at one time. Cloud-based with very easy access to current Imports or Exports, as well previous versions that had previously been run. You can see Imports or Exports across all time, even if you change filter criteria.

Incentivized

• Limiting the amount of data moving up and down from the cloud for cloud-native applications.
• Overall simple to use interface which is actually easier for a first time ETL developer than SSIS.

Incentivized

• HUGE time saving. When we need to clean or review data, we used to have to do it line by line. This can do the work within excel and make cleanup/management an afternoons work as opposed to a week.
• Rollback what you did/change/deleted is relatively simple if you remember to back up the data you are manipulating.

Incentivized