SSIS Reviews

We use SSIS to integrate investment data we collect from different places into our portfolio management system. We get results out of portfolio management systems and integrate that into the downstream back-office, risk, and regulatory reporting systems. All the developers at my company use it. 

SSIS is an easy way to do data integration from various data sources. It doesn't matter whether it's a database, flat files, XML, or Web API. It can talk to the and join them all together.

It's difficult to refactor SSIS. It gets cumbersome to reuse the solution. 

I have used SSIS off and on for maybe 15 years.

SSIS is stable. 

SSIS scales well

I've never had any issues with SSIS, but I'm not responsible for managing the solution at an enterprise level.

I've used free solutions or ones that allow you to create your own. I've used free ones like KNIME, etc. The open-source solutions have similar features, but I haven't found one with the same ease of use.

I've never had to install SSIS at an enterprise level, but the installation is straightforward for development purposes. It takes less than an hour. However, installing it at the enterprise level would require a lot more configuration, tuning, etc. I'll leave that to the experts.

We pay for a license, and I think SSIS is priced about right. 

I rate SSIS nine out of 10. 

We use this solution to ingest data to a data lake that is built on SQL Server.

SSIS seems easy to use, is freely available for programmers to learn on their own, and has a lot of resources on the web for any trouble you get into.

The most valuable features of this solution are the fast insert and fuzzy logic matching.

This may be done, but upgrades to new versions required re-implementing each package.  This is worse for us because we have about one thousand SSIS packages. Hopefully they are now allowing backwards compatibility.

Generic processes should be used instead of custom code for each table.

We are using SSIS for ETL and ELT in a business intelligence context. We bring in data from different sources and use SSIS transform and load it into our intermediate database where we are developing dashboards. There are three people doing configuration and about 50 end-users. 

SSIS provides you with lookup and transformation functions, and you have the flexibility to write your own custom code.

SSIS doesn't have a very good user interface, but if you can work with it, it'll provide you with almost all of the functionality.

We have been using SSIS for four years now.

The SSIS is highly stable, but there are occasional issues with the script component.

SSIS is not that scalable. You can scale it vertically to handle a high load, but it lacks horizontal scalability. 

Microsoft has some support for SSIS, but because the company is increasingly transitioning to the cloud, so these on-prem solutions are becoming obsolete.

The initial setup isn't too difficult, but it's not easy. Sometimes, you may need help from a database administrator to set up the SQL Server Integration Services. It can take almost a day to deploy. 

A database administrator can deploy it alone. You may need another person to develop the packages and set up ETL, so it's you need about two or three people for deployment in all. 

SSIS is included at no additional cost in the SQL Server license.

I rate SSIS seven out of 10. I would recommend using a cloud solution if possible, but if you need an on-prem product, SSIS is a good option. If you want to start using SSIS, there is a learning curve because SSIS isn't an easy solution to use. It's complicated, so you have to learn about the components and their functionalities to use them to meet your requirements. 

Our company sells contracts when you buy a car. We sell aftermarket insurance for the tyre, wheel, ding, dent, windshield, etc. When somebody buys a contract, we capture all of that data into a legacy database PostgreSQL, and my task is to incorporate that into our financial platform using T-SQL. So, I write queries, procedures, and views. I use SSIS, and I use SSRS. My job is to get the data into our financial system so that we can process claims, payments, cancellations, and refunds.

It's something I needed for bulk imports. I'm not a big fan of it, but I haven't seen anything better.

One of the problems I ran into was that the database that I had had a status. I couldn't always flip the status, so I didn't know what data I already had. I had to use SSIS to grab a bunch of data and check the database to see if I needed to insert it. It works okay, but as I plan better, I'm trying to weed it out. SSIS is a bit prickly because anytime you go and change something, it tends to break. That's because there is metadata behind the tool.

I have a tool called ZappySys. I need that tool to cut down on the complexity of SSIS. That tool really helps with a quick turnaround. I can do things quickly, and I can do things accurately. I can get better reporting on errors.

I'm not a fan of SSIS itself. I would rate out-of-the-box SSIS a four out of 10, but with the ZappySys tool, it is a pretty good solution, and then I would rate it an eight out of 10.

I'm using the solution primarily for e-memory and e-database calculation, mostly data blending (ETL) and massive table joining, etc. I also use it for data preparation and modeling.

With this solution, there is the potential to expand so that you can immediately write code onto the SQL server. Auto-parallelization is also critical for us. It decides automatically how many parallel sessions you have to run to get your query handled. You don't need to take care of any code, which is ideal. It's also highly scalable.  

The solution should work on the GPU, graphical processing unit. There should also be a piping integration available.

The design of the dashboard isn't great, visually, but the solution works, so this isn't so important to me.

SSIS's competitor, Autonomous Database by Oracle, offers you, depending on the performance of the server, new hardware, should you update your software. It advises you on how to optimize your system. It's AI and works as an artificial database manager. Microsoft doesn't have anything like this yet, but it would be nice if they did.

The stability of the solution is perfect.

The solution is very scalable. We have approximately 25-30 users for the on-premises version, and our cloud version has around 5,000 users.

We don't ask for much from technical support. We utilize community information, and source answers via the internet or online user information. I do find that communicating with Oracle is much better.

We previously used Oracle as an integration tool, but it's much more expensive than Microsoft.

The initial setup was easy.

We had a consultant that assisted us with the implementation.

I use the private cloud as well as the on-premises version of the solution.

I would rate this solution eight out of ten. I would rate it higher if the solution offered full automation AI for database managing, setup and management, and scaling of the solution.

SSIS orchestrates data transformation in the environment, which includes Oracle and SQL Server databases.

The most valuable aspect of this solution is that it is simple to use and it offers a flexible custom script task.

Connectivity to databases other than Microsoft. This is the Achilles' heel.

Integration with other vendors' connectivity should be available as well as being able to read and write data to databases or data storage other than with Microsoft.

There is connectivity with other databases, however, this is the most significant issue that has to be addressed.

I have been using SSIS for five years, but I first used it in 2007.

SSIS is quite stable.

SSIS is moderately scalable.

The company is fairly substantial. They have approximately 400,000 people in the company, but I am not aware of how many are using this solution. It is quite a bit.

There are a lot of developers using it.

I am not aware if they plan to increase their usage, it is not within my decision.

In terms of my immediate surroundings, we intend to use cloud tools, Azure technologies, and Microsoft. First and foremost, Microsoft ADF. Azure Data Factory is the cloud's SSIS replacement.

For this particular product, we have not used technical support.

I started with SSIS but then switched to IBM Datastage.

That was where I worked, this was already in use at another organization. 

I recently moved jobs, and this is the platform of choice for ETL once again. Informatica data center was used in various other organizations. 

I was attending Informatica workshops. I wasn't Informatica actively, but I might in the future, perhaps soon.

The initial setup is straightforward.

It only took five minutes to deploy SSIS. 

For maintenance, we rely on our platform team.

We will probably need one person for maintenance. Let's say it's only one person. But I'm not speaking on behalf of the entire company; I'm speaking on behalf of a single team of perhaps 1,000 people.

We did not use a consultant or third-party vendor, everything was done in-house.

This is difficult since it is included in the SQL server license. 

Depending on the arrangement that a certain company has with Microsoft, it may supply the permanent license that is included in the SQL server license, or it may be a time-bound license if it is a partner license or other enterprise license. 

I am not sure what our relationship with Microsoft is like or what the program is, but I believe it's some sort of enterprise license.

In the past, I worked with permanent licenses.

I would recommend SSIS to others who would be interested in using it.

I would rate SSIS an eight out of ten.

SSIS is mainly used for data migration transfer.

SSIS' best feature is SFTP connectivity.

In the next release, SSIS should include automated JSON file management.

SSIS is stable.

SSIS is scalable.

Microsoft's technical support has decreased in quality over the last few years, becoming less responsive and tending to pass problems on instead of solving them.

The initial setup is straightforward.

SSIS' licensing is a little high, but it gives good value for money.

I'd give SSIS a rating of seven out of ten.

We have used SSIS in many ways. Primarily, it has been used for building ETLs for populating data warehouse and staging areas. We have developed a number of data marts that were populated. We build data migration packages, which have been reused a number of times with minimal configurations. Additionally, we build complex data integrations solutions and data hand-offs between different applications. We have even used it for creating and parsing SWIFT messages for data integration purposes. We also used it for email triggers. 

Now SSIS has introduced Big Data and cloud components. Though we haven't used any of these yet but it's really a very good addition to enhance SSIS capabilities.

SSIS is a tool which anybody can learn in no time. When we started the project, the whole team learnt it in one week's time and then were ready to start on project tasks. It gives you control. Recently, we used SSIS for a compliance project where we performed data cleansing and extensive data transformations to prepare data files for use of compliance (Trade Based AML solutions) application.

Script task and Script component for custom tasks: It gives you power to build your own logic if your requirements are not being fulfilled with existing available components. While the big thing is you can build your own components, that is not so straightforward. 

It's visual design interface is good and you can easily understand the flow. 

The debugging capabilities are great, particularly during data flow execution. You can look into the data and see what's going on in the pipeline. It has good logging capabilities as well.

It should have other programming languages supported as well from a scripting perspective. Currently, only C# and VB.NET are supported, which limits it to .NET. It should have Java support as well. 

We couldn't explore big data related components, and this area should be up to the mark, if not already. Certain data quality checks should also be part of it. Currently, this is the biggest area that should be looked into. Data quality is an essential part of the integration process and ETL. Currently, only the data profiling task is there. 

As an update, now SSIS offers big data components as well. 

5+ years.

I've been using it for last 7 years in different projects for different banks. Didn't face any stability issues yet.

Yes. It's very much scalable, but it all depends on how you design your solution. SSIS provides you extensive features and toolkit to handle all sort of data problems.

I also used Oracle Data Integrator as an ETL tool but it all depends on your need and customer preference. SSIS is being easy to use and things can be developed very quickly so I prefer to use SSIS for most of my data related tasks.

Its setup is very easy. You don't need too many components to start building ETL tools. Plus, there are a lot of online learning available for this tool. It can be deployed on any Windows machine with minimal requirements.

If you have SQL Server License then you can use SSIS without any additional cost.

Overall, we remained in a good position and in control while using SSIS. We didn't face any challenges.