SSIS Reviews

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.

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 solution.

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 did not stay closer to SSIS for its Data Factory.

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 1 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 resolve the 3/4 without human Root Cause Analysis (RCA).  This leaves any failure after 2 retries the only issues that the night crew has to RCA and resolve.

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.

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.

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.

We are using it in our company and for our clients. I have experience in working with the whole data cycle, which includes data collection, transformation, and visualization. I have worked with the end-to-end process, and I have handled data integration, analysis, and visualization.

I specialize in Microsoft tools, and I have used SSIS for data integration and Power BI for data visualization. I have also worked with Tableau for data visualization and Talend for data integration.

The most valuable thing is that it is easy to connect with Microsoft tools. In Europe, particularly in France, a lot of companies use Excel, SQL Server, and other Microsoft tools, and it is easier to connect SSIS with Microsoft tools than other products.

It is also easy to learn and user-friendly. Microsoft is also good in terms of technical support. They have built a large community all over the world.

When I compare Talend and SSIS, Talend provides more features. With Talend, we can handle a large volume of data. Talend is usually used to treat a large volume of data, which makes it better than SSIS on the data side. 

Talend also has a very good Talend Management Console to schedule the jobs and do other things. It can also be easily connected to version control tools such as GitHub or SVN. The last time I used SSIS, it was connected through TSS for the Windows Console version. I am not sure it has been improved or not. If it is not improved, Microsoft should improve it. They should change the product to provide another console. 

Microsoft is good in terms of technical support. They provide 24-hour support. They have built a large community all over the world, and one can find easily the answer to an issue or problem by searching on the web.

Its installation wasn't my job. We have a team that specializes in infrastructure, and they install and set up the tool. When I was a student, I used to install it myself, and it wasn't really difficult, but I have not installed it on a professional site or for a company. 

Based on my experience and understanding, Talend comes out to be a little bit expensive as compared to SSIS. The average cost of having Talend with Talend Management Console is around 72K per region, which is much higher than SSIS.

SSIS works very well with Microsoft technologies, and if you have Microsoft technologies, it is not really expensive to have SSIS. If you have SQL Server, SSIS is free.

I would rate SSIS a six out of ten. I prefer Talend over SSIS.

We primarily use SSIS to collect data from one system and transfer it to another.

The Classical ETL processing of data.

It's a competent product. You can do a lot of things with it and learn how to use it. You can't do modern things with it, but you can do legacy things with it.

It is an out-of-date product, that we shouldn't be using anymore, as it no longer has many positive aspects.

It is an old tool. We make an effort not to use it. It's a legacy tool, that is nearing the end of its useful life. There could be some good things but we try not to get into that.

We have selected to go with another tool. SSIS should not be used whatsoever anymore. There are new versions, that are cloud-based, which are much more improved and much more feature complete.

We have been working with SSIS for 15 years.

We are working with the latest version. It hasn't been updated for many years.

I would say it's both reliable and stable. It's been on the market for 20 years, so it's a very mature product.

There are limitations. I wouldn't say that it is easy to scale. You can scale it, but I wouldn't say it can easily be done.

We have eight people who use this solution in our company.

Support is available, but it is no longer up to date. It needs to be improved.

We switched to Data Factory, which is the cloud version of SSIS and the primary reason for the switch.

Absolutely, the initial setup is a simple process. In my opinion, it's easy.

SSIS doesn't require any maintenance.

The deployment was completed internally.

It comes bundled with other solutions, which makes it difficult to get the price on the specific product.

It's actually a tool that we're attempting to eliminate. That should not be used. It's an old piece of equipment. That should not be used in any way.

If I was asked five or six years ago, I would recommend this solution, but not anymore.

I would rate SSIS an eight out of ten.

We have data that needs to be migrated. There is also a scan inventory. We create web data, pull it, search it, and then find answers and report stakeholders. So for this process, we use the SSIS.

You can get data from any data source with SSIS and dump it to any outside source. It is helpful. Getting, extracting, converting, and dumping data doesn't require much effort because we can do everything in the user interface. You drag and drop, then give the required input. It's intuitive.

Sometimes we need to connect to AWS to get additional data sources, so we have to install some external LAN and not a regular RDBMS. We need external tools to connect. It would be great if SSIS included these tools. I'd also like some additional features for row indexing and data conversion. 

We've been using SSIS for about four and a half years. 

If you run SSIS from the local system, it will lag, but it will work properly if you host on the cloud somewhere. It's a headache every time you run this locally.

Almost 10 percent of our users work with SSIS. It's more than a hundred. 

We haven't had that many problems. I have interacted with Microsoft support for some things, but it was a few minor issues. And with the updated VPA, it has been clear. I was satisfied with the support. We don't need support for these types of issues. We don't need to contact the support team or stop our business. 

The initial setup is never a complex process because the interface is user-friendly. If you are working with complex situations, then it can get complicated. We have a DBA team to handle the deployment. We must follow a process to deploy, so we need to get approval whenever there is a change. It's not easy for us, but it's still good, and it doesn't take much time. 

SSIS is on the cheaper side. In terms of value for the money, rivals are offering more database formats and cost processing, so SQL is lagging somewhat. 

I rate SSIS eight out of 10. I recommend it. 

Some of the valuable features I have found with this solution has been the variety of transformations that are possible and it works well with SQL servers. The majority of our clients that I worked for, their whole systems of data is using SQL server which has worked better for them.

The script component is very powerful, things that you cannot normally do, is feasible through C#. If you can write a script you can import it through the Script Task.

The solution could improve on integrating with other types of data sources. We had issues with connecting to Oracle, it did not do as good of a job as it did with SQL servers. 

In my experience, more efficiency is needed when it comes to dealing with huge volumes of data. However, this is also dependant on the server capacity.

In an upcoming release, they should update the features to facilitate efficient data transfers. 

I have been using the solution for approximately 10 years.

We have not experienced any behavioural differences with the operations of the solution, it is stable.

We typically implement the solution for enterprise-size companies.

The installation was easy.

It would be beneficial if the solution had a less costly cloud offering.

Informatica and Talent, are two options I am currently evaluating.

Customers have moved on pass SSIS and use Azure Data Factory, Databricks or something similar. We have a few of our customers looking to moving on to Informatica or Talent. This is how I was led to itcentralstation.com, to learn more about SSIS and how it was compared to Informatica. 

I have never had a situation where a particular transformation was not possible in SSIS. We have always been able to meet the demands of our need with SSIS.

I rate SSIS an eight out of ten.

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.