Azure Data Factory vs. Hevo Data

Azure Data Factory is a great data integration tool for developing a cloud data platform, especially within the Azure ecosystem. Azure Data Factory is very good for the Data Ingestion part. It can work for simple data transformation with its Data Flow, but it will also need cluster configuration, and there is some cost. Also, it is an excellent tool for orchestrating data pipelines. But for complex data transformations, you may need to use technologies like Databricks and PySpark.

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

• It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
• We can use linked service in multiple pipeline/data load.
• It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.

Incentivized

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

Incentivized

• Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
• Does not yet have parity with SSIS as far as the transforms available.

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 is more of a universal pipeline. SAP BW is a tool offering good SAP connectivity but very limited third-party connectivity. The same is the case with BW4hana. SAP Datasphere is offering better connectivity with SAP sources, but not so good when compared to adf. Power Center of Informatica is a legacy tool, and Anaplan is a planning tool with limited connectivity options.

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

• Cost Savings: By automating our ETL processes with Azure Data Factory, we've reduced manual data handling by approximately 60%. This translates to savings from reduced man-hours and the overhead of maintaining legacy systems.
• Timeliness: Our report generation time has reduced by 70% with Azure Data Factory's scheduled pipelines. Faster insights mean quicker decisions for us, enabling our teams to capitalize on time-sensitive opportunities. We can easily share the data visualizations to all stakeholders.

Incentivized

• Increased Time
• Decreased Failures
• Increased User Happiness

Incentivized