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Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.Good integration with MSSQLIt is mainly used by technical analysts with the purpose of delivering data integration and reporting projects to customers. It addresses the need for complex multi-source data ingestion, data manipulation, and integration to a MSSQL database.,Visual programming makes configuration easy and accessible The ability to code also allows users to implement complex logic for data manipulation and etc. Easy integration with MSSQL Database instances.,Component properties are not very well defined, which makes the learning curve harder As control flow and data flow often looking similar visually at first glace, it takes awhile to differentiate which one you are working on as users need to look at the tiny symbol and text on the tab to do so. A more straightforward color-coded or larger visual cue to differentiate between the two would make this easier.,8,As it is part of the SQL related products, customers are more receptive to the product due to the lower risk. This increased our product offerings in our solutions for projects. The work required to implement an SSIS project is relatively quick compared to other tools and it reduces the amount of time required by staff to configure.,Dundas BI,Dundas BI, camunda BPM, Microsoft SQL ServerSSIS is one of the best ETLsSQL Server Integration Services is used for the following purposes in my organization. 1. Extract data from the source database and transform it and then load it into a destination database 2. Use this for Balancing between 2 or more different databases 3. Extract the data from relational databases and load into data ware house.,Transform the data Lookups Performance,Script components are always a problem Cannot debug properly inside of Script component,9,Positive Impact: Faster Performance Negative Impact: Script Task and Script component always hangs up,Informatica Enterprise Data Integration,Informatica Enterprise Data IntegrationA solid ETL tool. Data doesn't stay in one place, SSIS keeps it going where it needs to go.Like most businesses, we have various sources of data that management likes to be able to compare to each other. I use SSIS primarily to move data between our source systems and data marts and warehouses that our reporting software can be pointed at. I also use SSIS to deliver scheduled file exports to external customers or to import files into one of our critical systems for use. I even tend to use it for non-SQL related things such as file system and ftp tasks. If it needs to be extracted, transformed, or loaded somewhere, I use SSIS to do it.,There are many good workflow tools and ways to control the order in which things happen. In a short amount of time, you can quickly create a package that will move data from point A to point B and have it scheduled to run 4 times a day. Or if you need error handling or other business logic, you can spend more time and completely automate repetitive tasks. Robust? Check! SSIS can consume multiple sources of data. From flat files, to Excel, to Oracle, or DB2...I've been able to access multiple data types and move them in and out of SQL databases with SSIS. We had one linux system that ran a Basis database system and there was a need to have something done, but no one could figure out how to make it work. I was able to use SSIS to import files and execute code on a server that had nothing to do with SQL server. So flexible? Check! We already use SQL server almost exclusively for our enterprise database needs. The fact that we already have access to this tool at no additional cost to the business is a bonus. The fact that it is powerful, even better. Value? Check!,I know in my "pros" comments, I said it was nice because we already had access to SSIS by virtue of being able to install it on existing SQL servers with no additional license cost. But, if you rely heavily on SSIS, you will want to have it on its own server rather than letting it share resources with a very active SQL server. That means additional licenses. It can consume a lot of resources, depending on the amount of data you're pushing through SSIS at any given time. Current versions of SSIS do a much better job of managing deployment of packages into production. It used to be an all-or-nothing proposition so if you had to make a small change to a project that had many packages in it, you'd have to redeploy the entire project which means lots of extra testing. The introduction of package level deployment was welcome. SQL server and SSIS play very well together when they have enough resources. If you're using virtual servers and can add CPU/RAM/Space easily, then by all means, put them together and manage the resources so they stay out of each other's way. If you don't have the capability to do that, then you'd be better off having SSIS on a separate server. When everything is working well, it is amazing. But if you make SSIS and SQL fight over resources, it's not pretty (SQL wins that fight by the way in case you were wondering!) If I'm being honest, I haven't had to point SSIS to a huge variety of source systems. It could be that SSIS doesn't play well with certain DBMS' (I've heard Sybase compatibility complaints before) and you'll need to do some research and testing before actually using it in production.,10,I use SSIS to automate tasks that I'm repeatedly asked to do. "Hey, can you go into the system and close any open orders that we've fully filled?" Sure....then I schedule a package to do that for me every hour so I'm never asked again. It saves me time, which gives value to the company. It removes the risk of human error. When people build files and send them, there's the risk that it doesn't happen the same way every time or gets forgotten. With SSIS, you spend some up front time building a process, but then you deploy it and forget it (unless it emails you that there was an error. You are putting error handling in your ETL, right?). Very repeatable and consistent business solution.Don't let SSIS rest if you already have it with SQL Server comboIn the beginning, we had hundreds of Stored Procedures, instead of SSIS packages. The Stored Procedures were poorly made by some users, only thinking on the resulting query and not the execution performance, plus the people doing data mining created tables for a report and then they didn't eliminate such tables that only had one use, also some of those tables kept growing without being needed any longer.The implementation and onboarding of SSIS was made with the intention to correct some of these T-SQL coding issues. It is easier to understand a diagram than sheets of T-SQL code with good documentation. Besides the performance for bulk inserts was better with SSIS than normal inserts in stored procedures. We were able to divide and define a bit better the roles, between SQL developers, Data miners, and BI engineers.,Logging, this is essential when you do ETL. With SSIS you can run the package and see step by step the progress, how many tuples complied with the filters, like how many went left and how many were correct, or excluded. Using regular expressions with C# direct code by adding Script Components it's easier with SSIS https://sqldusty.com/2011/11/06/data-cleansing-with-regular-expressions-in-ssis/ https://www.linkedin.com/pulse/using-regular-expression-file-filter-ssis-sean-werick/ Performance, it is difficult to demand good SQL code to every member of the BI team not everyone is specialized in T-SQL. SSIS standardizes a bit more the code and allows users not completely familiar with SQL or even C# to achieve what they needed, the package still needs to go through a code review but it is quite easier to understand.,Be careful when you edit a package, if the version is above the SSMS you are using then it will not be compatible. You have to compile or edit the SSIS package in the same version of SSMS you are using. To explain it a bit better if you have SQL 2014 in your laptop, pull a package for the DB server which is running SQL 2012, after you edit the package it will not be allowed in the SQL server. Python, Perl scripts are still a high competition for SSIS, mostly because they are very easy to manipulate, if you need a change you can do it directly with notepad. Plus Python now has an add-on called Pandas which is great for manipulating data.,9,It comes with SQL server, so if you are already using that for the DB, we had no charge for using SSIS for the same solution. That is one big advantage of Microsoft, they provide the whole combo for BI at once. ROI is a time measure, if you bought SQL just for the DB, but then you want to use SSIS, most probably it is already there. If you try even an open source solution, you will have to install it and get trained on it, for SSIS the learning curve is very short. Be careful, SSIS is for ETL, not for middleware at an enterprise level. In the begining it might work but it is not the purpose of the tool, for middleware solutions where the business depends on, don't get confused and if you are still looking for Microsoft go for BizTalk.,,TIBCO JaspersoftIf your back end RDBMS is SQL Server, SSIS gives you a bang for your buck.SSIS was being used as an ETL tool both by IT as well as business teams. It is now replaced by a competitor though. The tool was being used for basic extraction and loading purposes, with hardly any complex data transformation being done. Though there were use cases to exploit the tool, neither Microsoft nor in-house consultants really helped with the tool, with the result being it getting replaced.,Source systems connectivity (RDBMS, Flat Files etc) Embedding SQL and other code in case of complex business logic and data transformations Multitude of data transformation options Ease of use, easy to learn Skills availability in the market,version control/configuration management Programmatic issues like NULL handling (it's RDBMS counterpart SQL Server database uses NULL differently) The source connectivity options should be enhanced,8,It wasn't used effectively, resulting in not realising ROI to the extent we had anticipated It was easy to learn, which resulted in business teams using it extensively without IT support, resulting in lots of packages/code to maintain,Informatica Enterprise Data Integration, IBM InfoSphere Information Server and Oracle Data Integrator,Informatica Enterprise Data Integration, Oracle Data Integrator, IBM InfoSphere Information Server,250,10,Simple extraction and loading self service data integration complex transformations,None, with the version it was then,None really,6,No,Price Product Features Product Usability Existing Relationship with the Vendor,Things have changed now and there are more use cases to consider than what we had considered years ago. It's a different ball game now. We might do it grounds up this time,9,Don't remember instances,Pretty much everything is easy to use,complex transformations which SSIS can't really handle,No,8
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SQL Server Integration Services
152 Ratings
Score 7.9 out of 101
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SSIS Reviews

SSIS
152 Ratings
Score 7.9 out of 101
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June 21, 2018

SSIS Review: "Good integration with MSSQL"

Score 8 out of 10
Vetted Review
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It is mainly used by technical analysts with the purpose of delivering data integration and reporting projects to customers. It addresses the need for complex multi-source data ingestion, data manipulation, and integration to a MSSQL database.
  • Visual programming makes configuration easy and accessible
  • The ability to code also allows users to implement complex logic for data manipulation and etc.
  • Easy integration with MSSQL Database instances.
  • Component properties are not very well defined, which makes the learning curve harder
  • As control flow and data flow often looking similar visually at first glace, it takes awhile to differentiate which one you are working on as users need to look at the tiny symbol and text on the tab to do so. A more straightforward color-coded or larger visual cue to differentiate between the two would make this easier.
SSIS is suitable for MSSQL related projects/works due to how well it integrates and performs data manipulation. It is suitable for moderate data input ingestion rates but not suitable for projects where a high volume of data is required to be ingested and processed rapidly.
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July 16, 2018

User Review: "SSIS is one of the best ETLs"

Score 9 out of 10
Vetted Review
Verified User
Review Source
SQL Server Integration Services is used for the following purposes in my organization.
1. Extract data from the source database and transform it and then load it into a destination database
2. Use this for Balancing between 2 or more different databases
3. Extract the data from relational databases and load into data ware house.

  • Transform the data
  • Lookups
  • Performance
  • Script components are always a problem
  • Cannot debug properly inside of Script component
SQL Server Integration Services is best when we use it with Microsoft SQL server database
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Greg Goss profile photo
April 06, 2018

Review: "A solid ETL tool. Data doesn't stay in one place, SSIS keeps it going where it needs to go."

Score 10 out of 10
Vetted Review
Verified User
Review Source
Like most businesses, we have various sources of data that management likes to be able to compare to each other. I use SSIS primarily to move data between our source systems and data marts and warehouses that our reporting software can be pointed at. I also use SSIS to deliver scheduled file exports to external customers or to import files into one of our critical systems for use. I even tend to use it for non-SQL related things such as file system and ftp tasks. If it needs to be extracted, transformed, or loaded somewhere, I use SSIS to do it.
  • There are many good workflow tools and ways to control the order in which things happen. In a short amount of time, you can quickly create a package that will move data from point A to point B and have it scheduled to run 4 times a day. Or if you need error handling or other business logic, you can spend more time and completely automate repetitive tasks. Robust? Check!
  • SSIS can consume multiple sources of data. From flat files, to Excel, to Oracle, or DB2...I've been able to access multiple data types and move them in and out of SQL databases with SSIS. We had one linux system that ran a Basis database system and there was a need to have something done, but no one could figure out how to make it work. I was able to use SSIS to import files and execute code on a server that had nothing to do with SQL server. So flexible? Check!
  • We already use SQL server almost exclusively for our enterprise database needs. The fact that we already have access to this tool at no additional cost to the business is a bonus. The fact that it is powerful, even better. Value? Check!
  • I know in my "pros" comments, I said it was nice because we already had access to SSIS by virtue of being able to install it on existing SQL servers with no additional license cost. But, if you rely heavily on SSIS, you will want to have it on its own server rather than letting it share resources with a very active SQL server. That means additional licenses. It can consume a lot of resources, depending on the amount of data you're pushing through SSIS at any given time.
  • Current versions of SSIS do a much better job of managing deployment of packages into production. It used to be an all-or-nothing proposition so if you had to make a small change to a project that had many packages in it, you'd have to redeploy the entire project which means lots of extra testing. The introduction of package level deployment was welcome.
  • SQL server and SSIS play very well together when they have enough resources. If you're using virtual servers and can add CPU/RAM/Space easily, then by all means, put them together and manage the resources so they stay out of each other's way. If you don't have the capability to do that, then you'd be better off having SSIS on a separate server. When everything is working well, it is amazing. But if you make SSIS and SQL fight over resources, it's not pretty (SQL wins that fight by the way in case you were wondering!)
  • If I'm being honest, I haven't had to point SSIS to a huge variety of source systems. It could be that SSIS doesn't play well with certain DBMS' (I've heard Sybase compatibility complaints before) and you'll need to do some research and testing before actually using it in production.
If you need to move data around or direct the workflow of a process, SSIS can do it. It is a very capable piece of software that I use heavily every day. You do need to be careful because you can over-utilize it for simple things. If you just need to run a piece of SQL every hour to update some values, just use the Agent Scheduler, it's easier. But if you need to automate things in a repeatable and consistent manner, SSIS is a very good product.
Read Greg Goss's full review
Jose Pla profile photo
March 02, 2018

Review: "Don't let SSIS rest if you already have it with SQL Server combo"

Score 9 out of 10
Vetted Review
Verified User
Review Source

In the beginning, we had hundreds of Stored Procedures, instead of SSIS packages. The Stored Procedures were poorly made by some users, only thinking on the resulting query and not the execution performance, plus the people doing data mining created tables for a report and then they didn't eliminate such tables that only had one use, also some of those tables kept growing without being needed any longer.

The implementation and onboarding of SSIS was made with the intention to correct some of these T-SQL coding issues. It is easier to understand a diagram than sheets of T-SQL code with good documentation. Besides the performance for bulk inserts was better with SSIS than normal inserts in stored procedures. We were able to divide and define a bit better the roles, between SQL developers, Data miners, and BI engineers.

  • Logging, this is essential when you do ETL. With SSIS you can run the package and see step by step the progress, how many tuples complied with the filters, like how many went left and how many were correct, or excluded.
  • Using regular expressions with C# direct code by adding Script Components it's easier with SSIS
  • https://sqldusty.com/2011/11/06/data-cleansing-with-regular-expressions-in-ssis/
  • https://www.linkedin.com/pulse/using-regular-expression-file-filter-ssis-sean-werick/
  • Performance, it is difficult to demand good SQL code to every member of the BI team not everyone is specialized in T-SQL.
  • SSIS standardizes a bit more the code and allows users not completely familiar with SQL or even C# to achieve what they needed, the package still needs to go through a code review but it is quite easier to understand.
  • Be careful when you edit a package, if the version is above the SSMS you are using then it will not be compatible. You have to compile or edit the SSIS package in the same version of SSMS you are using.
  • To explain it a bit better if you have SQL 2014 in your laptop, pull a package for the DB server which is running SQL 2012, after you edit the package it will not be allowed in the SQL server.
  • Python, Perl scripts are still a high competition for SSIS, mostly because they are very easy to manipulate, if you need a change you can do it directly with notepad.
  • Plus Python now has an add-on called Pandas which is great for manipulating data.
Extracting, transforming and loading data from multiple sources with different formatting is not that easy. SSIS provides different ways to connect or import from html, json, comma separated, xml, or other databases, which makes it a very diverse tool.

The only main competition I have noticed is the combo of Python, Pandas, and Jupyter; but for that other solution, you will need an experienced team in scripting. So at the end is choose what your team feels more comfortable.
Read Jose Pla's full review
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April 27, 2018

Review: "If your back end RDBMS is SQL Server, SSIS gives you a bang for your buck."

Score 8 out of 10
Vetted Review
Verified User
Review Source
SSIS was being used as an ETL tool both by IT as well as business teams. It is now replaced by a competitor though. The tool was being used for basic extraction and loading purposes, with hardly any complex data transformation being done. Though there were use cases to exploit the tool, neither Microsoft nor in-house consultants really helped with the tool, with the result being it getting replaced.
  • Source systems connectivity (RDBMS, Flat Files etc)
  • Embedding SQL and other code in case of complex business logic and data transformations
  • Multitude of data transformation options
  • Ease of use, easy to learn
  • Skills availability in the market
  • version control/configuration management
  • Programmatic issues like NULL handling (it's RDBMS counterpart SQL Server database uses NULL differently)
  • The source connectivity options should be enhanced
If the back end RDBMS is SQl Server and if you are migration from Oracle or DB2 to SQL Server, SSIS does the migration job very well. It's tightly integrated with SQL Server. However, issues like NULL handling etc persists. Also, if the integration platform has unsupported connectivity or drivers, then SSIS usage becomes challenging.
Read this authenticated review
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February 15, 2018

SSIS Review: "Great ETL tool"

Score 8 out of 10
Vetted Review
Verified User
Review Source
We currently use SSIS for imports of purchase orders into our ERP - SYSPRO. These purchase orders come in various file formats: EDI, XML and excel spreadsheets. SSIS helps us aggregate these various files into a common import platform and apply business logic such as ship date calculations, SKU availability checks, customer hold checks etc.
  • Great for parsing data from various file formats into SQL server. As an example, we use it to extract data from XML, EDI and other flat files.
  • Great for applying custom business logic in the ETL process. These business logic could be built into functions, stored procedures and applied through the SSIS packages.
  • I like it's exception handling capabilities and how it's able to show the module that threw up the exception by highlighting it in red.
  • Works very well with Visual Studio and as a matter of fact, you can build all your SSIS packages right from SQL without even opening up SQL server or BIDS.
  • Not sure if it has JSON support but if it does, that would be awesome! Basically, the ability to consume data from a JSON data set.
  • In as much as Microsoft built it for the SQL database, it would be awesome if we could leverage SSIS for data ETL into other databases like MySQL and Oracle etc.
  • Add more color themes! The default color theme is old school and really sucks if you ask me.
1. Great for ETL (Extract-Transform-Load) data operations.
2. Amazing if your primary database environment is SQL server.
3. Works great with Visual Studio and Microsoft even has it now on the Azure platform.
4. Works great with various file formats - XML, EDI, spreadsheets, flat files etc.
5. Works great in scenarios where it is necessary to apply business logic through stored procedures etc.
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Eddie Brady profile photo
August 10, 2017

User Review: "SSIS"

Score 9 out of 10
Vetted Review
Verified User
Review Source
I've used SSIS to support individual departments within an organization. Typically I use SSIS to automate migrating and transforming data from one location to another. SSIS has a diverse range of source and destination formats that makes it easy to move data between different systems. There are many add on tools for other source / destinations that are not out of the box. For example, Dynamics CRM.
  • SSIS allows you to run many processes in parallel. Thus, you can run multiple data flows simultaneously to increase the throughput of the migration process.
  • SSIS provides many tools for transforming data during the migration process.
  • The one issue that I have with SSIS is that sometimes the business logic gets baked into the SSIS package. This can make it harder to debug. In some cases this makes sense if the source and destination is not a database. However, when using a database as a source I prefer to manipulate and transform the data via sql and then simply expose the dataset to SSIS after the data has been prepared. I find it easier to write and debug sql directly rather than working in SSIS. However, in cases when a database is not involved then putting the business logic in SSIS makes sense.
SSIS is well suited for any processes that can be automated to move data from a source to a destination. However, I don't think SSIS can work directly with Rest API's during it's processing. If that is required than it would be necessary to build your own custom SSIS component to enable this functionality. Extending SSIS to permit this is possible.
Read Eddie Brady's full review
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July 19, 2017

Review: "SSIS offers what I need for data processing."

Score 8 out of 10
Vetted Review
Verified User
Review Source
In my current organization, SSIS is being used by the enterprise data warehouse team. This team uses SSIS to construct data warehouse, prepare data cubes, and fulfill ad-hoc data-related acquisitions.
  • Presents the flow of data processing very well, making it easy to learn/understand SSIS packages.
  • T-SQL and C# friendly.
  • Comprehensive configuration, logging, and error handling.
  • Some components are not working very well, including sorting, SCD, etc.
  • Different components could have different syntax or data type definition.
  • Not enough scripting learning materials.
For SQL Server users, SSIS would be a natural yet very wise choice. It works quite well with Microsoft bottom layer and offers an easy and more user-friendly way of manipulating data.
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David Milillo profile photo
March 29, 2017

User Review: "SSIS Addict"

Score 8 out of 10
Vetted Review
Verified User
Review Source
Integration Services is the primary extraction, transformation, and loading tool we use to populate our SQL Server and Azure SQL DB and DW for our data and our clients' data. We do a majority of our logic for preparing both reporting and application data within SSIS components, scripts, or within T-SQL Stored Procedures executed within SSIS Control flows. It is only used within my group but my group is the only group directly populating our reporting databases.
  • Native data connections to SQL Server and Azure SQL DB and DW
  • Flat file processing
  • .NET C#/VB scripting
  • Ease of use in designing and implementing control flows within conditional processing and looping
  • Integration with Access/Excel should be more seamless and less problematic
  • CASS certified address standardization
  • Higher performing Slowly Changing Dimension functionality
  • SFTP
  • Incremental loading (deletion, upsert, etc.)
  • PowerBI integration. I really really really want to be able to refresh reports via IS packages
  • More Azure administration tasks
  • Office365 and Sharepoint integration
Well suited:
  1. Full refresh loading files (Excel and Flat File) into SQL Server.
  2. Integrating .Net (VB/C#) scripting
Less suited:
  1. Incremental loading
  2. OLAP database loading
Not suited:
  1. Streaming, real-time/near real-time loading
  2. Big data loading
Read David Milillo's full review
Hung Nguyen profile photo
August 05, 2016

SSIS Review: "Use it if you have a Microsoft Stack"

Score 8 out of 10
Vetted Review
Verified User
Review Source
I cannot say for the whole organization, but we use SSIS for just about all our automation processes. When managing a large data warehouse it is incredibly useful to automate the ETL process. We primarily use it for the data warehouse, but it's versatile enough to use for other automation tasks, reports, and notifications.
  • Clear GUI and ETL workflow. It's very easy to understand how the data is being managed. When pulling up a SSIS solution that someone else has created, it's very easy to see what's going on-- how the data is extracted, how it is transformed, and how it's being loaded.
  • Deploying scripts. Once a proper package store is configured, you just need to hit deploy and it handles the rest. It's also flexible enough that you can still use SSIS packages without using an SSIS DB for version control by calling them through the file system. Or if you're one of those people who love batch scripts, you can also execute the packages through command line.
  • SSIS Package Store. It's a great way to manage your versions and deployments. Bonus is that if you use a package store, it'll also give you error reports after the fact if a package fails for debugging. It'll tell you exactly what step failed and why.
  • I think it handles undefined/dynamic data sources poorly. Considering that we use it primarily to ETL data from other systems across the whole organization to bring into our BU's data warehouse, we sometimes have issues when the source has changed. If someone adds a column without letting us know, we'll need to modify the SSIS packages.
  • Sometimes the error codes are vague or cryptic. When debugging a SSIS package I have to google the code or error message and hope someone has a similar issue on stack overflow.
  • SSIS really only works if you're already using a lot of Microsoft Products like Microsoft SQL Server or SQL Server Reporting Services. As mentioned in the name of the application, "integration services", it's designed to integrate your products together so that you can get the most out of it.
As mentioned in the pros and cons, SQL Server Integration Services is great when you're running a Microsoft stack. We're loading data from all over into our data warehouses and moving them between other SQL instances all the time. I can whip up a package and deploy it in less than 5 minutes to get our data moving between SQL servers. It integrates really well and is flexible enough that you can supplement any lacking functionality using third party plugins or building your own tools. Although this has been solved in later iterations, SQL Server Data Tools (which is used to build SSIS packages), did not have the functionality to download files from an FTP server using SFTP. I built a C# app that I could run using SSIS.
Read Hung Nguyen's full review
Eugene LaRoche profile photo
June 03, 2016

User Review: "SSIS- Mundane but Dependable"

Score 7 out of 10
Vetted Review
Verified User
Review Source
SSIS is utilized as a systems and data integration tool, and for performing a variety of ETL tasks. It is utilized by the IT department to support business applications, particularly where two or more systems require data exchange. It is a mature product (stable and reliable) and comes as part of standard SQL Server implementations so its fairly simple to utilize.
  • SSIS Integrates very well with other Microsoft products including Excel and Access. Other ETL tools may have a difficult time integrating with Access, so we have observed SSIS to be superior in this regard.
  • SSIS has the capacity to do a fast bulk load (BCP) with transformations, within the bulk load itself. This feature is not available when utilizing the BCP utility outside of SSIS or from other ETL tools. To be clear, the transformation is occurring within the BCP component itself. Other ETL tools will have to utilize a non-BCP load (slower) or do the ETL after the load. This is a great feature I have not seen replicated in other tools.
  • SSIS integrates seamlessly with SQL Server RDBMS, including SQL Jobs and Stored Procedures.
  • SSIS has nice support, tools, and wizards for fixed length file processing.
  • SSIS IDE (SQL BIDS) is lacking, particularly when compared to Visual Studio for .NET development. It was carried over (at least in look and feel) from the legacy DTS tool. It could use a complete redesign from scratch. Considering how superior the VS .NET IDE is, the inferior SSIS BIDS IDE is unacceptable.
  • SSIS is very Microsoft centric. This is a strength when dealing with pure MS technologies, but becomes a weakness when dealing with disparate, distributed systems, including cloud computing. Other ETL tools for example easily integrate with everything from AWS to Google Drive to Sales Force.
  • SSIS deployment model is clunky and non-intuitive.
SSIS is best suited for use in a pure Microsoft environment, or where interfaces to external systems are file based. It is not ideal for integration into disparate systems that are not interfaced via flat file. SSIS is also ideal when utilizing the job scheduler built into SQL Server, as it is seamlessly integrated with SSIS. In other words, it's very easy to schedule an SSIS package to run automated using the SQL job scheduler. Running SSIS packages from other job schedulers is more problematic, unless that tool has built in SSIS support.
Read Eugene LaRoche's full review
Chris Morgan profile photo
May 26, 2016

Review: "SSIS is terrific for all your ETL needs."

Score 10 out of 10
Vetted Review
Verified User
Review Source
Our laboratory uses SSIS to transfer data between servers and databases, to data warehouses, reporting services and to and from file sources in a complex SQL Server environment that includes Merge Replication and SQL Server Reporting Services. Besides internal transfer, transformation, and manipulation of data, including archiving of data, we use SSIS to export laboratory results to external systems and import scheduling and sampling information from external systems.
  • SSIS can query, filter, and transfer data between databases on different servers without establishing explicit trust relationships between those servers.
  • SSIS can be used to refresh a reporting database from a transactional source database, transforming or flattening the data and tables as necessary to facilitate reporting. This can be done incrementally, or by emptying and refilling the reporting database from scratch.
  • SSIS is configured through graphical interfaces that make it relatively easy to see the flow of data including where problems occur.
  • SSIS has a number of tools that allow you to debug SSIS packages and track down problematic data or configurations.
  • SSIS allows you to program Script Tasks in C# and VB allowing extremely powerful functionality including looping and sending consolidated alerts.
  • SSIS allows you to control virtually every part of the SSIS package (connections, variables, etc.) using configuration files so you can have one package that can be used in several different places (such as dev, test, and production environments) only by editing the configuration file that the package uses when the job is scheduled.
  • One of the most frustrating things about SSIS, at least in its 2008R2 incarnation, is that of the annotations. Formatting annotations, getting them to wrap in the box, etc., is either extremely difficult or impossible without editing the XML of the SSIS package. You also CANNOT copy and paste annotations, so if you have several similar ones, you have to type every one of them from scratch. It makes you want to scream.
  • In the 2008R2 incarnation, setting up tasks to pivot data is very tedious and non-intuitive. I have heard that this improved in SSIS 2012, along with performance. We are trying to upgrade our SSIS and SQL server environment to 2012 or 2014 as soon as possible.
  • Sometimes datatype conversion doesn't work implicitly when it should and you have to do it either explicitly with a query or with a datatype conversion task.
Whenever you are moving data from one database to another, either on the same server or a different one, SSIS is a great tool. This is true for one-time transfers because it is so easy to set up and configure what you want to happen, and it is true for automated transfers that occur every day or every hour. If complex transformations of the data are necessary, including filtering, generation of new columns, merging datasets, whatever, SSIS is the best tool out there for ETL. If the task takes place within a database or between databases on the same server, and the task can be accomplished with a simple SQL script, it will often perform much faster than an SSIS package and require fewer server resources.
Read Chris Morgan's full review
Samir Patel, PMP profile photo
July 15, 2016

Review: "SSIS fits perfectly in Microsoft environments"

Score 8 out of 10
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SSIS is our main ETL tool since we are mostly a SQL Server shop. We use it to integrate data into all of our reporting environments, transforming and massaging data dynamically and connecting to many various sources along the way. It is also a quick way to move data out of other Microsoft environments such as Excel and Access Database.
  • Transform data
  • Issue Logging
  • Event Notification
  • Needs more connections to environments such as Hyperion
  • Not as robust as Informatica
  • No built in metadata management

When dealing with Microsoft environments, it is the tool that is easiest to use and implement. When it comes to connecting to Oracle Hyperion or pushing data to non Microsoft environments there can be challenges.

SSIS allows for quick implementations where the flow and environment is not too complex or large.

Read Samir Patel, PMP's full review
Waheed Abualrous, MCP, MCTS, MCE profile photo
May 23, 2016

Review: "SSIS is great if when used in the right place"

Score 8 out of 10
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Ee create master data management and workflow software for oil and gas companies which involves getting and writing data to other systems. We use SSIS for all integration as it helps dealing with different systems.
  • Makes it very easy to move data form one system to another
  • So many out of the box transformations
  • The script task gives you so much flexibility as you can write C# code to do almost anything
  • Easy deployment and configuration after the 2012 release
  • Project deployment model to allow deployment of single packages
  • Allowing to apply one transformation on all columns, like changing all column types from nvarchar to varchar instead of doing it one by one
  • Mamed parameters from inline SQL statments using OLEDB command, currently they are called parameter 1, parameter 2...etc., which is confusing when you have many paramters
  • Pass authorization tokens when calling remote processes like a console application, currently being called as anonymous
if you don't have an Sql Server license or are deploying to any OS other than Windows you need to consider a different technology.
Read Waheed Abualrous, MCP, MCTS, MCE's full review
Tom Jaskula profile photo
May 06, 2016

SSIS Review: "A Reliable Data Preparation Tool."

Score 8 out of 10
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SSIS is used by the IT department for extracting, transforming, and loading data. The most common application for SSIS would be for cleansing and restructuring data while it is being loaded into a data warehouse.
  • Providing developers with a wide range of architectural options.
  • Providing the ability to connect to a wide array of data sources.
  • Proving many different deployment options.
  • While SSIS does provide a plethora of architectural options, all of these options can at times be overwhelming. Some competing products offer a more straight forward and streamlined approach.
  • SSIS does not currently provide any templates, although this is supposed to be addressed with the upcoming release of SQL Sever 2016
  • Connecting to Oracle databases is not easy, SSIS still requires the installation of other tools.
SSIS is a good fit when you have structured data. If you're looking to prepare unstructured data for doing text analytics, this is not the right tool.
Read Tom Jaskula's full review
Luca Campanelli profile photo
April 15, 2016

SSIS Review: "A high-performance ETL product"

Score 9 out of 10
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In our department we use SQL Server Integration Services daily. The main use is to do data processing for several ETL processes. Thanks to the use of SQL Server Integration Services we can upload data to the data warehouse in different ways such as a bulk load or with incremental loads thanks to the use of SCD task data.
  • High data load speeds
  • Many data processing modes
  • Many data sources and destinations data possible
  • For some tools you need to integrate third-party packages
  • Depending on the version you must have the right visual studio version to develop and deploy
  • Not really intuitive
SQL Server Integration Services is optimal for any process of data extraction, data transformation and data loading, and can be used quickly for massive loads. It can be used for scheduled and incremental processes. It is not optimal for data structures that continuously change their structure because in this case it requires continuous changes and deploys.
Read Luca Campanelli's full review
Elena Goryainova profile photo
February 23, 2016

Review: "SSIS is ETL's best buddy for skilled SQL Developers"

Score 10 out of 10
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SSIS is a powerful tool to perform various ETL-like functions between homogenous and heterogeneous sources of data. It was widely used in all organizations I worked since it provides an easy way to create data transformations.
  • Easy connection configuration
  • Powerful wizard for data mapping
  • Native exception handling
  • User-friendly interface
  • Easy to learn
  • Package can be deployed via Visual Studio
  • Requires programming experience for custom tasks
  • Shell version of VS used for SSIS package development doesn't support C# as scripting language (needs at least professional edition)
  • Some tasks are hard to debug, aren't they?
I definitely recommend it. The only thing is that you have to be skilled to design a good package architecture otherwise support may be hard especially during migrations to the newer versions of SSIS engine (had that problem in the past).
Read Elena Goryainova's full review
Shrikanth Mahale profile photo
October 30, 2015

SSIS: "The Review"

Score 8 out of 10
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Verified User
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It is been used in the entire department to support enterprise analytics and reporting
  • User friendly
  • Compatible with windows
  • Cheap and good for mid size companies
  • Needs to be capable to hold large data
How large is my data and how much can my company spend.
Read Shrikanth Mahale's full review
Pancratius Mukeh profile photo
October 29, 2015

User Review: "SSIS Cheap and easy to use"

Score 7 out of 10
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We use SQL Server Integration Services to pull data from FTP sites.
  • Our clients have branches and each branch generates a flat file and loads to a remote site from which we pull and consolidate the data and report from the consolidated data.
  • SSIS would allow [us] to execute a batch file which will pull the files and decrypt.
  • SSIS transformations are easy to use when [they] loop around the files in the same folder.
  • SSIS expressions are difficult to read and comprehend.
  • SSIS fuzzy loop up transformation performance needs to be optimized.
  • SSIS packages code should be easy to copy and modify so that it can easily be replicated just like BIML.
Can SQL Server Integration Services (SSIS) perform multiple unrelated tasks within a package?
Read Pancratius Mukeh's full review
Nurvin Flowers profile photo
October 27, 2015

SSIS: "SQL BI Stack review"

Score 7 out of 10
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Verified User
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Used across the organization to move data, develop data marts and build front end reports
  • There is flexibility to Transform various data. There are also templates that help to guide you in using best practices such as building TYPE 2 loading of Data Warehouse tables
  • There are many transformation features that allow for sorting, lookups, using a variety of data sources and targets. It is a full featured product.
  • There are a lot of properties that allows you to customize data flows to suit your needs.
  • Having to sort prior to merging is a pain.
  • Working on very large data sets approaching 1 billion records require a lot of pre-planning. Teradata handle large data sets better
  • Error messaging is sometimes not explicit enough. "Something went wrong" is one of my "favorites" that I have seen
Well suited for data sets that are not too large < 500,000,000. Not well suited for handling very large data sets.
Read Nurvin Flowers's full review
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June 04, 2016

User Review: "SSIS - Our go to ETL Tool"

Score 9 out of 10
Vetted Review
Verified User
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SQL Server Integration Services is the go to tool for our Data Integration team for automating a number of disparate data imports. We deal with a number of file sources (Excel, CSV, TXT, etc) that need data transformed for import into our SQL databases. SSIS allows us to handle any number of file formats and types efficiently, and we can perform all data validations necessary to ensure utmost data integrity.
  • Handling upsert functionality (i.e. performing lookups against existing data to determine new versus existing records).
  • Automation of scheduled file imports. Essentially any consistent data source can be automated after a one-time SSIS package is set up.
  • Ability to handle a wide variety of data sources.
  • Excel data type handling - makes assumptions on a single data type where there might be multiple data types in a specific column.
  • Better handling of data schema changes - If you have column changes or additions in your data source, it does not always implicitly make those changes across all data transformation tasks within the package.
  • No reliable built-in functionality for SFTP connections.
SQL Server Integration Services is particularly well suited for automating oft-used data transformation processes. Any transformation tasks that are performed manually on a consistent data source should be able to be automated using SSIS. It's also very well suited for DB to DB data migration, whether it be one-time ad-hoc requests or common scheduled tasks (i.e. migrating from test to production databases).
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April 28, 2016

User Review: "SSIS - A great ETL solution!"

Score 9 out of 10
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SSIS is used by a lot of people within our technology department, but it is used heavily by our developers. We utilize this tool to move data between servers as an alternative to using a linked server and also to migrate data into our production systems from third party databases.
  • We use SSIS as a tool to help convert and migrate data from third party systems into our internally developed CRM system.
  • We use SSIS to move data from server to server, where a linked server is not present.
  • SSIS allows us to import tables directly from other sources (Access, Excel, etc.) to our Microsoft SQL environments.
  • SSIS is utilized to export data from our SQL servers into Access database backups for our clients who request backups of their data.
  • Although it's better than the old DTS, I think some more default integrated data sources/targets would be beneficial.
  • Integration with MySQL would be great. Currently we have to use Microsoft SQL Server Migration Assistant for MYSQL to get this done. If this was integrated into SSIS, it would alleviate the need for the other program.
SSIS is great for ETL projects, for exporting/importing data into MS SQL, and for moving data between servers. It's an excellent tool for those types of projects and scenarios.
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October 27, 2015

Review: "SSIS, an ETL tool with a lot of hidden benefits!"

Score 10 out of 10
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We are using SQL Server Integration Services for mission critical import, export, and data transformations. It is being used across the whole organization for various business processes. Since we receive numerous file transfers, we have to create many SSIS packages and projects to import, and process the files. In addition, we send numerous files to clients.

We are also using SSIS to transfer data within our environment from server to server. When replication is not required, we prefer to use SSIS to transfer data at specific intervals to reduce overhead on the servers.

  • File import and export
  • Data transfer from source database to a destination database
  • Database Maintenance tasks
  • Data cleansing improved
  • Additional database source connections
SSIS is used most commonly in a SQL Server Environment. I have seen SSIS used in non SQL Server Environments strictly for the integration portions. SSIS is well suited for file transfers, data transfers, database maintenance, and various business processes that you are looking to automate. The SSIS scheduling allows jobs to run on specific schedules.
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October 28, 2015

Review: "SQL Server Integration Services is one of the best ETL tools out there"

Score 7 out of 10
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Verified User
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We use SQL Server Integration Services for Cube processing. It's being used by my department.
  • Cube processing packages
  • ETL
  • DBA tasks
  • Metadata Management
  • Big Data support
It works really well with other Microsoft products like SQL server and SSAS.
Read this authenticated review

Feature Scorecard Summary

Connect to traditional data sources (24)
9.1
Connecto to Big Data and NoSQL (19)
7.1
Simple transformations (24)
9.3
Complex transformations (24)
8.0
Data model creation (11)
7.1
Metadata management (14)
6.6
Business rules and workflow (17)
8.6
Collaboration (18)
6.9
Testing and debugging (22)
8.2
Integration with data quality tools (20)
7.7
Integration with MDM tools (18)
7.7

About SSIS

Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
Categories:  Data Integration

SSIS Technical Details

Operating Systems: Unspecified
Mobile Application:No