Data Virtuality Platform vs. SQL Server Integration Services (SSIS)

Data Virtuality Platform's best and most unique feature is
that it is SQL-based, giving us flexibility when working with our data that
other marketing integration pipeline tools couldn't provide. Our main benefits
are the short time it takes to connect to our data sources and the flexibility
of the virtual SQL layer to meet our end users' data needs. It paves the way
for us to tap into various data repositories, extract the data contained
within, and examine it. It allows us to access information, generate actionable
reports, and make data-driven decisions. However, inadequate data governance
rules and a complex configuration process make data connectors challenging.

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As I mentioned earlier SQL Server Integration Services is suitable if you want to manage data from different applications. It really helps in fetching the data and generating reports. Its automation make it very easy and time efficient. It works well with large database as well. But it doesn't work well with real time data, it will take some time to gather the real time data. I would not recommend using it in a real time/fast-paced environment.

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• ETL/ELT model building is flexible.
• The pipes' setup and use are intuitive.
• It lets us access various data sources, extract, and analyze data.

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• Standard ETL use cases for daily loads
• Loading incoming data from Vendors which is placed on FTP and adding them to the SQL Warehouse
• Creating outgoing data files and writing them to Vendor FTPs
• Easy Active Directory integration for seamless connections to SQL Server
• CI/CD by hosting the code on visualstudio.com

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• Configuring data connectors can be tricky.
• Price could be more flexible and adapt to the use case.
• The ETL builder's user interface could be prettier.

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• Connection managers for online data sources can be tricky to configure.
• Performance tuning is an art form and trialing different data flow task options can be cumbersome. SSIS can do a better job of providing performance data including historical for monitoring.
• Mapping destination using OLE DB command is difficult as destination columns are unnamed.
• Excel or flat file connections are limited by version and type.

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Some features should be revised or improved, some tools (using it with Visual Studio) of the toolbox should be less schematic and somewhat more flexible. Using for example, the CSV data import is still very old-fashioned and if the data format changes it requires a bit of manual labor to accept the new data structure

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SSIS is a great tool for most ETL needs. It has the 90% (or more) use cases covered and even in many of the use cases where it is not ideal SSIS can be extended via a .NET language to do the job well in a supportable way for almost any performance workload.

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SQL Server Integration Services performance is dependent directly upon the resources provided to the system. In our environment, we allocated 6 nodes of 4 CPUs, 64GB each, running in parallel. Unfortunately, we had to ramp-up to such a robust environment to get the performance to where we needed it. Most of the reports are completed in a reasonable timeframe. However, in the case of slow running reports, it is often difficult if not impossible to cancel the report without killing the report instance or stopping the service.

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The support, when necessary, is excellent. But beyond that, it is very rarely necessary because the user community is so large, vibrant and knowledgable, a simple Google query or forum question can answer almost everything you want to know. You can also get prewritten script tasks with a variety of functionality that saves a lot of time.

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The implementation may be different in each case, it is important to properly analyze all the existing infrastructure to understand the kind of work needed, the type of software used and the compatibility between these, the features that you want to exploit, to understand what is possible and which ones require integration with third-party tools

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Data Virtuality Platform has powerful transformation and
scheduling capabilities combined with the best support team. A virtual data
layer that supports SQL procedures is a game changer. Data Virtuality has made
data management more efficient. It lets us access various data sources, extract,
and analyze data. The short time it takes to connect to our data sources and
the flexibility of the virtual SQL layer allows us to meet our end users' data
needs.

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Independently Invited by TrustRadius

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I think SQL Server Integration Services is better suited for on-premises data movement and ADF is more suited for the cloud. Though ADF has more connectors, SQL Server Integration Services is more robust and has better functionality just because it has been around much longer

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• It has the capability of integrating data from a variety of different sources.
• It improved development and user interface to offer a robust MDM repository and strategy.
• It offers a comprehensive solution for processing and retrieving data, which is one of the ways it assists.

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• Without this, we would have to manually update a spreadsheet of our SQL Server inventory
• We would also have poor alerting; if an instance was down we wouldn't know until it was reported by a user
• We only have one other person who uses SQL Server Integration Services , he's the expert. It would fall to me without him and I would not enjoy being responsible for it.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info