Azure Data Factory vs. Google Cloud Storage

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

[Google Cloud Storage is] great for storing and playing large video files, and even sharing them securely with others, whether or not they are part of your organization. No need to download video files before watching, and can also be used to store any other kinds of files.

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

• Really great, easy to use interface helps us manage files easily. Storage is fast and inexpensive, so we don't have to spin up storage instances locally
• Great set of command-line tools to manage data and storage options via scripts and apps, as well as an SDK means we can build GCS into our orchestration and operations tools
• Robust integration with other Google cloud tools means that we don't have to think too hard about using GCS for a variety of storage tasks as we interact with other Google services.

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

• Sometimes we would find advice for how to do something that wasn't documented in the API, although this was very early on.
• When we first started using it, Google Cloud Storage was changing a lot, and some of these changes required us to adapt our code to fit them.

Incentivized

after all of the investment made in the tool and considering how many teams use it I think we would not be likely to move away from this tool. A lot of our information including historical is already here and we are happy with the capabilities of the tool currently

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

I would rate Google Cloud Storage’s usability as excellent, particularly for developers. The web console is clean and intuitive for basic tasks, while the CLI tools offer powerful automation. Although navigating IAM permissions has a slight learning curve, the comprehensive documentation and seamless integration with other Google services make it highly efficient.

Incentivized

For performance i give Google Cloud Storage 10 of 10 on performance because even though there are other softwares that do exactly the same thing as Google Drive, it still works exceptionally well. It is very fast, and and far as integration, the only software I have used with it that integrated was Google Docs, and of course it integrates perfectly.

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

We have never used official support from Google for our Google Cloud Storage, but there is plenty of documentation in place already. With a small amount of work, anybody should be able to get started. Once needs get more complicated, there is still documentation from Google, but also plenty of community support for common use cases around the internet.

Incentivized

overall I was not directly involved but hears the teams were satisfied with the implementation. the teams that used the tool did not encounter major issues, it was as expected with minor issues and bugs that were resolved later. The more significant learning curve was actually starting to use the tool

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

Google Cloud Storage compares very similar to Dropbox. The difference of using Googe Cloud Storage is that it is part of a big bundle of products that you are probably already using. If you are a big Google user then it would make sense to get Google Cloud Storage. This way you can have all of the tools you need under one roof. I selected Google Cloud Storage because I was already using Google's other products and I was very impressed by those products so it was an easy sale.

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

• It allows the use of large Big Query data sets, this enables better data analysis.
• It helps the business maintain a central storage solution for data.
• Secure and easy to learn and use, it allows for fast adoption which improves productivity.
• It does not enable collaboration and has limits on flexibility.

Incentivized