Azure Data Factory vs. Hevo Data

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

Hevo Data is professionally sound in data management and credible analytical processes, where there is proper sourcing and data connectivity, from the different sources. Further, Hevo Data brings huge transformation and analytical approaches, which increases the viability of every operation in the company, and results are credibly issued. The integration that Hevo Data provides is comprehensively sound, and it gives quality coordination.

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

• 5 Minute Sync with Salesforce
• Transformations
• Auto Schema Mapping
• Push to Salesforce

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

• If we are getting data from other sheets then sheet which is connected to Hevo Data doesn't updates in real-time.
• Hevo Data change time in it's workbench on its own. For e.g. If our database timestamp is in UTC format then Hevo Data will automatically change the time to IST but if I run the same code outside the Hevo Data workbench then time is still in UTC. This creates lots of confusion while working on Hevo Data.

Incentivized

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

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

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

1. Cost efficient 2. Creation of automated pipeline 3. Can load data from multiple data sources 4. Updates data in near real-time - We were able to get near real time insights from the data model which we have created in hevo 5. It has good integration with different BI tools

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

• Increased Time
• Decreased Failures
• Increased User Happiness

Incentivized