SSIS Reviews

Presently, we have decommissioned the solution. Earlier, we used SSIS with the SQL Server.

The most valuable feature of the solution is performance. It works by connecting to the SQL Server.

Integration and the user interface are areas with certain shortcomings that require some improvements.

I have been using SSIS for more than fifteen years.

Stability-wise, I rate the solution an eight out of ten.

It is not a scalable solution. You have to replace it.

There were five users of the tools in my company.

I have never contacted the solution's technical support team.

I have not used any other product that is similar to SSIS.

Some experts need to be involved in the deployment process, which is straightforward and easy to manage.

The product's setup phase was straightforward.

The product's deployment phase was easy.

People have to opt for a perpetual-based licensing model.

It can be useful for data integration across different sources since it is a stable product.

In terms of a complex data transformation process you've managed, the tool offers some accesses associated with integration services.

The data warehousing capabilities of the tool benefited our company, and it is one of the good things about the solution because there are different databases that you can access throughout the process to collect information as you desire.

Our company can recommend the tool depending on the client's requirements. We are using it for data warehousing and collecting some information from the database. Nowadays, there are probably different solutions that can do that efficiently and effectively.

The debugging and error handling capabilities of the tool improves our company's data integration task but it is very challenging. The people who use the tool to work have mentioned that debugging issue is a bit difficult for them.

I think it would be better if people could check out other solutions available in the market and compare them to SSIS.

I rate the tool a seven out of ten.

SSIS (SQL Server Integration Services) is primarily an ETL tool. It's frequently used for data integration and transformation. In the past, we used it to integrate data into our systems. Microsoft is now focusing on Azure Data Factory for cloud solutions, but SSIS is still a viable on-premises option.

SSIS utilizes SQL Server Management Studio (SSMS) for management. I've used SSMS for many years and find it quite user-friendly, even for those new to SQL Server.

Being a Microsoft product, it integrates well with Visual Studio, a familiar development environment. It also has a graphical interface that displays the ETL process step-by-step. 

It's a familiar tool within the Microsoft ecosystem, which has its advantages. 

It lacked robust cloud integration and sometimes struggled with specific data types from sources.

Another area of improvement is performance. It has always been an issue. 

I used it for more than ten years.

It is a stable product. I would rate the stability an eight out of ten. 

I don't believe SSIS is a major development focus for Microsoft right now. Performance enhancements are always a concern.

Scalability mainly depends on the underlying SQL Server installation. A more powerful server can naturally handle larger data volumes. There might be performance bottlenecks specific to SSIS itself.

There are around two to three end users in my department. There might be more in the company. 

I usually resolve issues on my own.

The setup was easy. All Microsoft products are easy to set up. 

It comes with SQL Server. We didn't have a separate license for it.

It does its job. I'd probably rate it a six out of ten. Performance could be better.

SSIS is a good fit if you're heavily invested in on-premises Microsoft products. If you have a more diverse tech stack, better ETL tools might be available. Microsoft often limits how its products interact with others.

We have a consolidated data warehouse. We use an SSIS tool as a pipeline to fetch the data from multiple sources such as Excel, CSV, Oracle database, or APIs. Further, we put the data into the SSIS database. We are using the solution for ETL purposes.

Previously, it took a lot of work to connect with multiple data sources. But now, we can connect with them easily using an external connector in SSIS.

Sometimes, we have issues with SSIS connectors while extracting data from Excel sources. They should improve this particular area for excellent compatibility.

I have been working with the solution for the last ten years.

It is a very stable solution. We have been creating a solution in SSIS, deploying it into the server, and scheduling it using SQL Server jobs. All the jobs have been running easily and quickly for the last ten years.

It is a scalable solution. I have around 800-900 users of the solution in our organization.

As I have been using the solution for the last ten years, I directly highlighted some questions to Microsoft. It is very easy to reach out to them, and I always receive support from them.

We used Informatica as well. We switched to SSIS as it took a lot of work to set up a pipeline in Informatica. Also, SSIS is more straightforward for the end user. 

The solution's setup was straightforward. It takes a day or two to complete the process. If you are good at development, the deployment process becomes easy. You only need a few resources to deploy the solution. I am handling deployment and maintenance all alone.

The solution is available at a lesser price than that of Informatica. I assume SSIS's enterprise version of SQL Server is pretty costly, but I must be aware.

The solution is easy to maintain. SSIS is a handy tool but requires vast knowledge to build the pipeline using it. I advise others to go for SSIS if the user is versed in developing a pipeline. Otherwise, you can quickly build a pipeline using multiple user-friendly solutions.

I rate the solution as a ten.

We primarily use the solution for getting the data from the application database and to the OLAP system. We extract the data from OLAP system and build data warehouses. Basically, this solution is used to build OLAP.

This tool works well when users aren't working with large amounts of data. 

It is easy to set up the solution. 

SSIS is very, very, very slow. It hangs a lot of the time. There is a buffer issue and a memory issue.

You need to keep a lot of packages. There's a lot of maintenance. 

The design is not user-friendly. 

They need to include a lot of connectors, and their component should be much faster. The component, transformation component, like lookup datatype conversion, doesn't work well for large amounts of data.  

I've been using the solution for two and a half years. I've used it for a while. 

It is quite stable. It's safe and reliable. A lot of organizations are using it instead of Azure Cloud.

I'd rate the scalability four out of ten. The solution does not handle large amounts of data well. Azure Data Factory is much, much more scalable. 

We've also used Azure Data Factory, which is much faster than SSIS.

The initial setup is not difficult. However, when the volume increases, it slows down. It's a bit of an obsolete tech stack and is not very current.

You only need one person the setup and deploy the product. 

We handled the initial setup in-house. We did not need outside assistance when handling the setup. 

I'm not aware of the exact pricing. It's being handled by another team. 

We're using Visual Studio 2019 and SQL Server Integration Services 3.16.

I'd advise potential users to go and learn Azure and use that. Use Data Factory, not SSIS. 

I'd rate the solution six out of ten. 

Mostly we are receiving files in either XML or Excel and then we collect them in databases. Sometimes it's CSV and sometimes it is also Excel. Mostly, it is XML.

We have many regulations that we must follow, and this solution helps us manage that. There are rules that we must follow, and we get files in a uniform structure, and we need to import them into databases. Doing it with SSIS saves us a lot of time.

The performance is better than doing it in some alternative ways. We don't have to worry about so much manual work. 

Mostly it was helping us with importing XML files by checking the access and then doing some look-ups and containers to implement loops and things like that mostly. That was quite helpful in terms of saving time. 

Technical support is helpful.

No big improvements are needed at this time. 

At one point, we did have to purchase an add-on.

Since we are not using it for a whole ETL, or for a data warehouse, maybe I'm missing something.

I've been using the solution for almost eight years. 

The performance is very good. It makes it easier to do things that you would have to do differently otherwise.

I'd rate the overall stability eight out of ten. We haven't had any stability issues in many years. 

The scalability is pretty good. I'd rate the ability to expand at a seven out of ten. 

There are only three of us using the solution at this time. 

We contacted technical support maybe once. I don't remember when it was, however, once, we had to look at some dump size, and we called Microsoft to help us with that. They did help us, however, it was a very long time ago and I don't remember too many details about the problem or experience. 

While we are using it quite a lot, my understanding is that the company will go with Talend and not SSIS for a data warehouse project. I don't have any influence on that.

That said, we are not going to do any conversion from SSIS to Talend on what exists in our existing project. The data warehouse will be a totally new project, and they will go with Talend.

We did not use any other solution previously.

The initial setup is very easy. I'd rate it an eight out of ten in terms of ease of implementation.

The deployment itself only took a couple of hours. 

The installation that comes with SQL just requires some tweaking with Visual Studio or something like that. We had some problems with maybe deploying the product from the local machine, however, in the end, we solved it.

We have three people handling the initial setup. All of us are DBAs.

We handled the initial setup ourselves, in-house.

There are occasionally add-ons for SSIS that may increase the price. 

In the past, we did not evaluate any other solutions. 

We are end-users. 

The SQL version that we are using is 2019. However, I'm not sure about the exact version of SSIS we're using. We installed it with the 2019 version.

I'd rate the solution eight out of ten. 

In my experience with SSIS, I have found its most valuable features to be its package management capabilities and the flexibility it offers in designing workflows. We often use templates, inheriting and embedding scales in SSAS to streamline our processes.

In upgrading SSIS, we encountered challenges fixing SQL Server and performance issues, including problems during a failover in our data warehouse. After resolving these issues and conducting load balancing tests, we proceeded with the SSIS upgrade, anticipating potential complications. 

I have been working with SSIS for almost ten years.

I would rate the stability of SSIS at a solid nine out of ten. While there may be occasional encounters with bugs or performance issues, personally, we haven't faced significant problems in our usage. 

I would recommend SSIS for both smaller and larger companies. We operate as a small to medium-sized enterprise with a considerable volume of data, around 30 to 40 terabytes in our data warehouse. Despite being an SME, SSIS has proven effective in handling our ETL processes seamlessly. If an organization has a similar data size, around the 30 to 40-terabyte range, SSIS can be a suitable and reliable choice for managing their data integration needs.

Microsoft's technical support has been good, especially for critical issues in a financial institution like a bank. The bank receives strong support from Microsoft, and there is a significant level of accountability. If any issues arise, particularly those impacting financial operations, Microsoft is obligated to address and resolve them promptly.

While executing tasks and managing data flow, we occasionally encounter Oracle system integration, and in the past, we have used Antunica, though it seems Microsoft's support for it has dwindled in recent years. Despite some versioning challenges, our workflow design, execution, and deployment have been relatively smooth using SSIS.

SSIS implementation has been straightforward for us, using scheduled tools like Kubernetes for deployment and master packages in SSIS. It seamlessly integrates with Microsoft products and other databases like Oracle or Teradata. We haven't faced issues integrating with third-party solutions, and even with tools like Attunity, it has worked reliably for almost a decade without performance problems.

The pricing of SSIS is generally considered reasonable in comparison to other data integration tools in the market. In terms of licensing, I find Microsoft's pricing policy generally favorable, especially when comparing it to other products like Power BI. Microsoft's pricing is competitive, and they seem to have a good strategy, as evident in the success of Power BI. Over the years, SSIS has gained recognition, and Microsoft's promotion efforts have been effective. 

If you are considering alternatives to SSIS, I have worked with ODI in the past during consulting engagements. Colleagues have praised Informatica as a superior solution to ODI and SSIS, though I'm not aware of its pricing. While SSIS is lauded for its simplicity, there might be disadvantages compared to competitors like Informatica. However, our data warehouse team is highly satisfied with SSIS, and it is widely used in the industry. It is a common and reliable ETL tool with easily accessible solutions through internal resources and online searches, making problem-solving straightforward.

For those interested in SSIS, my advice is to go for it because it is a simple and effective solution. Even without deep knowledge, there are ample resources, including comprehensive documentation from Microsoft. Exploring their documentation provides access to numerous samples and best practices, making it user-friendly, especially for developers. So, don't hesitate to leverage the available materials and give it a try. Overall, I would rate SSIS as an eight out of ten.

We use SSIS to copy production data to Reporting Repositories. We use it for data movement from and to SQL or flat files such as CSV or fixed data.  This is primarily to build and update a data lake and data warehouse. 

More custom use cases are to do DQ validation comparing source to destination, and to extract data from bat files and SSIS files in order to build a metadata repository for documenting and mapping all the ETL packages.  We use this to find the packages responsible for any particular table or file, or vice versa.  This system, along with statistics logging, also gives us summary reporting capability.

I like that SSIS lets us build programs top-down. Starting with the control section, then drilling into the details of the steps make more sense than what Informatica requires, where you have to build each block first, then use a different tool to build the control structure.

In production, SSIS does a very good job of distributing work to many threads. It is robust and does a good job of handling overload conditions. It is simple for basic jobs, yet able to do very complex tasks. When all else fails, code can be written to make your own custom task or even tool.

I believe SSIS is not given the credit it deserves. SSIS does what most other new vendors tout as great features. But it is a very mature and stable product, unlike those others. It is supported by a larger company than many of those other products.

The error messages are pretty clear and point you to the problem well.

I am disappointed that Azure Data Factory did not stay closer to SSIS.

Data Flows are the main component we use. These can range from a simple source to sink ETL, to many source to many sink dataflows.

For flexibility and to make reading the logs in case of errors, I prefer not to put multiple copy operations in the same dataflow, although that is possible.  I try to keep in mind how to make production operations as easy as possible in case of failures.  I want to give the night crew the best opportunity for success when an error does occur.

We have about one error per 400 processes. About 3/4 of these were transitory issues with issues like slow connections and temporary outages. By making the code rerunnable, we can auto-restart on any error, and that resolves 3/4 without human intervention. This leaves any failure after two retries the only issue that the night crew has to do Root Cause Analysis (RCA) on.

We purchase an add-on called task factory primarily to allow bulk delete, update, and upsert capability. I'd like to see this be part of the standard package.

I believe there are ways to build a model and set variables so that it can be a generic process.

In my next system, I would like to have a generic process that would handle all the logging and processing in a model that can be modified and enhanced as the need for a better process, or different statistics to be logged is discovered.  I'd want this in a way that the model can be changed and all the processes, with their unique parameters, could all be changed with the model upgraded.

I believe they should add some features that help to create the code using a model. This would allow for continuous improvement of the model uses and easy replication of all the different programs that use the model.

15 years

Very mature and stable, and already has great performance features.

It can be very scalable both by adding memory or cores, and by running the SSIS on a farm of servers.

I did not really need much.  SSIS has a lot of excellent help available for a web search.

Positive

Prior solutions used SQL triggers

We have more control over the ETL with SSIS.

Installation is quite easy.  There are some drivers and setting you may need to make, based on the sources or sinks you need.  I am hoping these are more embedded in the install process, as I have not set up a server since 2015.

In house.  

good

SSIS is part of SQL server, in itself a very solid product.

You can run SSIS on the same SQL server instance where your data warehouse is, using the compute power at night to update, and during the day for reporting and data analysis.

I did not evaluate other options.  SSIS was available, and it worked well.

I later changed jobs to another company that used SSIS, and worked to improve and grow their data warehouse solution.

After using SSIS, we have tried talend, informatica, and spark solutions.  I would go back to SSIS, even for a non Microsoft shop, if I were allowed to.

It was used for a couple of purposes, for example, we used it in our data warehouse when we wanted to create a dashboard that would give us an idea about, for example, the data itself. We had a client that would ask about a couple of requirements, like the past data from the last month or last year for a particular region for a particular client, and so on. I was using SSIS to store data incrementally and show the data using SSIS. 

For example, if we have created a couple of tasks or schedules, we would create a couple of packages and schedule them overnight. Every night it could fetch the data incrementally from the data warehouse. Every week, there was a requirement from the client that I need to add particular data to be changed and shared over email weekly. That particular data could be fetched from the data warehouse, and it will be shared with the client every week. 

Many features are very good in SSIS. 

I can create a particular package, and I don't need to repeat it again and again. For example, I can create a package that will fetch all the data from the given data. If my client gives me some data, I can clean some data, perform some transformations, and then store the data in any place. That's quite helpful for me as well. I don't have to do it again and again manually. I just have to create a package, schedule it, and it could be run, and it could be stored in any target I have. It can run for me, again and again, without me having to re-make it manually again and again.

It is easy to set up the product.

There are a couple of areas that could be improved. For example, if I created a package and the package would work on specific data, it could work on the performance or speed of the action. If you are working on a very large amount of data, then creating this package and performing some transformations might take some time. Everything just needs to be faster.

I haven't used SSIS for the last year, so I'm not sure about its new releases as of now.

In terms of its performance, it could be better. That could be something that would be easy and welcomed as an upgrade.

I'd like to see more dashboarding to be able to see the data through a graph. It would be great if I could also share the visualization with my clients.

I did use it in my previous organization for almost one year.

It is quite a stable product. There are no bugs or glitches, and it doesn't crash or freeze. It is reliable. I'd rate it a three or four out of five in terms of stability.

There are six teams using the solution in our company. 

I've never had to reach out to technical support. 

I'm not using Palantir Gotham. I just read about Palantir Gotham, and I'm not using it.

One of my clients wants us to use SSIS, and frankly speaking, if given the opportunity, I would say yes to using SSIS.

With SSIS, it is not difficult at all to set up. Many sources are there through which you can learn how to set up your SSIS. The documentation is great. With the help of documentation, it was very easy for me to set up.

Deploying a package would also not take a lot of time. It depends on what kind of package it is, however, it is pretty fast.  

I'm not aware of the exact cost of the solution. 

I was a user. 

If you want to perform some transformation or data warehouse and the product is used for data analysis purposes, it's a good option. You can perform some transformation, et cetera.

I'd rate the solution eight out of ten. It was very useful for day-to-day tasks.