SSIS had its day, but in the big leagues it can no longer play
SSIS pulls data from various locations (mostly SQL Server instances but also some flat files and SFTP), mainly for transforming the data …
Overview
What is SSIS?
Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
Recent Reviews
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Popular Features
- Connect to traditional data sources (53)8.888%
- Simple transformations (53)8.585%
- Complex transformations (52)7.777%
- Testing and debugging (48)6.161%
Pricing
N/A
Unavailable
What is SSIS?
Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Would you like us to let the vendor know that you want pricing?
26 people also want pricing
Alternatives Pricing
What is Clear Analytics?
Clear Analytics is a business intelligence solution that enables non technical end users to perform analytics by leveraging existing knowledge of Excel coupled with a built in query builder. Some key features include: Dynamic Data Refresh, Data Share and In-Excel Collaboration.
What is Vertify?
VertifyData is a cloud-based integration platform with core integration capacities, including a drag-and-drop interface and real-time synchronization. It also offers over 80 prebuilt connectors and templates, plus customizable integrations for scaling businesses.
Product Demos
Demonstration of Multicast transformation in SQL Server Integration Services (SSIS)
YouTube
SSIS Tutorial Part 78- What is Multicast Transformation in SSIS (Quick Demo)
YouTube
SSIS Tutorial Part 119-Execute SQL Task (Full Result Set) Demo in SSIS Package
YouTube
SSIS Tutorial Part 72- What is Conditional Split Transformation in SSIS (Quick Demo)
YouTube
SSIS Tutorial Part 02- How to Load Tab Delimited File To SQL Server Table in SSIS Package
YouTube
Features
Return to navigation
Product Details
- About
- Tech Details
- FAQs
What is SSIS?
SSIS Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Frequently Asked Questions
Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
Reviewers rate Connect to traditional data sources highest, with a score of 8.8.
The most common users of SSIS are from Mid-sized Companies (51-1,000 employees).
Comparisons
Compare with
Reviews and Ratings
(259)Attribute Ratings
Reviews
(1-25 of 26)Companies can't remove reviews or game the system. Here's why
We use SQL Server Integration Services (SSIS) as part of our on-premise Data Warehouse architecture. We have an ELT pattern and SSIS is used almost exclusively for the Extract and Load steps. Almost all packages are generated using BIML (Business Intelligence Markup Language) as a means of templating and then scripting them.
- Easily connect with a wide variety of sources.
- Provide control and flow to job execution order.
- Able to extend functionality through scripting tasks.
- Not flexible when source/target tables and file formats change.
- Inflexible with regards to varying data types when Excel spreadsheets are used as a source or columns are added (as per previous item).
- Occasional issues around mixed development and production x86/x64 run times can be frustrating.
June 24, 2022
Good for startups or companies with limited data variability, Big data companies will need better tools
SQL Server is the legacy Database and Data Warehouse in the company. SSIS is used for most ETLs where the data is sourced from / put into SQL Server, depending on the use case. It is an MS native and easy-to-use ETL tool that comes with the SQL Server Data Tools suite. I use the tool personally to deploy ETLs for business stakeholders as a request arises.
- Standard ETL use cases for daily loads
- Loading incoming data from Vendors which is placed on FTP and adding them to the SQL Warehouse
- Creating outgoing data files and writing them to Vendor FTPs
- Easy Active Directory integration for seamless connections to SQL Server
- CI/CD by hosting the code on visualstudio.com
- API connections are not a native functionality. We use Zappysys extensions but they work only in certain cases.
- Dependency executions - no simple way to create a hierarchy/chain of executions. Ex: Define if the execution of the child process should be stopped if a parent fails or a certain condition is triggered in the parent process and then redirect to a different part of the chain (think like a flowchart for executions).
June 24, 2022
Tool for data integration and migration
In our organization, we have two Microsoft windows servers. We integrate their data sync via SQL Server Integration Services. It's easy for us to migrate our data from one server to another server. The debugging capabilities are great, particularly during data flow execution. We can look into the data and see what's going on in the pipeline.
- Encrypt files with SSIS and send them to various network locations this way we solve complex business problems.
- We can migrate DTS packages to SSIS while choosing to run DTS packages using DTS runtime or incorporate DTS packages into SSIS this way we migrate DTS packages to SQL Server Integration Services.
- We can transform data to make sure it complies with the rules of the database they are migrating to other servers with Integrations Services.
- User-required automation needs much more scope.
- Exporting numerous tables in CSV format has to be done one by one by manual.
June 23, 2022
SQL Server Integration Services (SSIS) is a winner and helps solve many business problems effectively.
We used Integration Services to extract and transform data from a wide variety of sources such as XML data files, flat files, and relational data sources, and then load the data into one or more destinations. We also used the graphical Integration Services tools to create business solutions for the firm.
- Create Packages in SQL Server Data Tools
- Reuse Control Flow across Packages by Using Control Flow Package Parts
- Build Integration Services User Interface
- We can improve Integration Services error messages, including a list of most Integration Services errors and their description.
- Improvement to create custom event handlers for these events to extend package functionality.
- Better support for tools and wizards helping with Legacy Package Deployment.
December 08, 2021
Provides value to cost and excellent with MSBI Stack, But needs more features/updates
SQL Server Integration Services has been useful in implementing Extract, Load, and transform logic from various sources and destinations. we also use it to download data files from SFTP, FTP locations. We use it to refresh extract in tableau and run other 3rd party services via executing process tasks. It has been useful to address many other such challenges.
- FTP Downloads.
- Run 3rd party softwares.
- Intuitive UI.
- Need more connectors/sources/destination components.
- Ability to support not just Microsoft services but others too.
- More updates & new features.
May 01, 2021
SQL Server Express + SSIS basics
We are using the SSIS as a major data export/import & converter between different data sources, including relatively old legacy stuff out from 90th. The beauty of SSIS is really advanced capabilities of data converts and mix up the data from different sources with all respect to keys and data relations. We use this mostly as an addition to the SQL Server Express edition (as a part of the import/export wizard) but on the sandbox I doing the tests of SQL Server 2016 Standard edition to mix up several RDBMS for data extraction into one data warehouse.
- Extraction and convert data from various sources
- Pipelining in the data extraction process
- Unions between different data sources akin one meta datasource
- Some labels in Visual Studio snap-in for MS SQL Server are collapsed on non-English (German & Russian tested) locales.
January 19, 2020
Great Tool For ETL Design
In my department, we design and manage ETL processes. We use SQL Server Integration Services (SSIS) to design a data warehouse. To create a data warehouse, we can make the stage layer and DWH layers with the SSIS ETL tool. We create data marts using aggregate functions in the SSIS ETL tool. In addition, we use the SSIS ETL tool to move data between databases.
- Data migration is pretty fast.
- SQL Server is highly compatible with the database.
- We receive errors in moving JSON data to the database. It does not work efficiently in JSON-related data.
- ODBC connections give a connection error after a certain period of time.
November 24, 2019
Our use of SSIS
We use SQL Server Integration Services to import data into and out of our main SQL server databases. This data comes from a variety of external sources and sometimes there is data format mismatch between source and destination. With an SSIS package, we can retain the mapping and data formats integrity from the source to the destination without having to go through the process every time.
- Easy to manage projects and packages.
- Ideal for repetitive tasks.
- Can handle complex tasks consisting of multiple, diverse packages.
- Include SSIS in the default installation of SQL.
- The flexibility and different packages and options can make it confusing for first-time users.
- Recommendations in the selections could make it easier to build a solution.
October 13, 2019
SSIS enables you to build the data lake of your dreams!
The IT department at our organization uses SQL Server Integration Services. We use SSIS to perform extract, transform, and load (ETL) data operations. Our primary use is to move data from a source system or database, restructure the data to optimize it for reporting, and store it in a database instance used for reporting.
- Handles multi-step, complex data moves.
- Pulls from a variety of data sources.
- Add-ons are readily available to extend their usefulness.
- Integration with SQL Server and data tools.
- The package publishing feature has gotten better over the years, but it could still be simplified.
- Incorporating features from add-ons into the standard application would be helpful (mostly in relation to data sources).
- Easier configurations for multiple publishing targets (dev/test/prod) with associated data connections.
We are currently using SSIS packages on two major projects:
1. To populate our data warehouse. Running SSIS packages from the server on a 10-minute schedule, we extract, transform and load the data into the warehouse to support all internal reporting and provide data as a service to our global partners.
2. Bulk data import to our CRM system. Building packages to run on-demand to bulk import structured data to our CRM instance.
In the past, we have used SSIS packages to complete a one-time migration from a legacy CRM system to the current CRM.
1. To populate our data warehouse. Running SSIS packages from the server on a 10-minute schedule, we extract, transform and load the data into the warehouse to support all internal reporting and provide data as a service to our global partners.
2. Bulk data import to our CRM system. Building packages to run on-demand to bulk import structured data to our CRM instance.
In the past, we have used SSIS packages to complete a one-time migration from a legacy CRM system to the current CRM.
- Ease of use - can be used with no prior experience in a relatively short amount of time.
- Flexibility - provides multiple means of accomplishing tasks to be able to support virtually any scenario.
- Performance - performs well with default configurations but allows the user to choose a multitude of options that can enhance performance.
- Resilient - supports the configuration of error handling to prevent and identify breakages.
- Complete suite of configurable tools.
- Connection managers for online data sources can be tricky to configure.
- Performance tuning is an art form and trialing different data flow task options can be cumbersome. SSIS can do a better job of providing performance data including historical for monitoring.
- Mapping destination using OLE DB command is difficult as destination columns are unnamed.
- Excel or flat file connections are limited by version and type.
Even though we are a smaller company, we use this huge army Swiss knife to accomplish a number of technical IT tasks. First and foremost we use it to integrate systems like MS CRM and SAP, constantly enhancing the data flow and making tasks easier to accomplish for the users. Secondly, I personally use it clean up data and maintaining my BI ETL scripts running out 12-year-old data warehouse for our analysis cube. The actual tool is currently only in use by the IT department by using Visual Studio (BIDS).
- Almost no programming is needed, like drawing simple flow diagrams.
- If you want to be more advanced you can add some VB or C# programming if needed.
- Microsoft tool using all the great connectors, using any data source
- Easy to add a third part like Cozyroc
- File handling
- Integration with office tools could always be improved, MS, as usual, provides these 80% solutions to make room for third vendors.
- Error message or event handling, better messages and link to processes.
January 15, 2019
SQL Server Integration Services: a great tool for small to medium sized implementations
SSIS is used within my organization to move data from one data source to another, performing data translations, transformations, lookups and calculations during the data movement. This process often includes very complex data transformation processes including the use of APIs, external references and various class libraries. SSIS is currently used in various areas across the entire organization to solve SQL server-based data transformation issues.
- It handles SQL Server databases flawlessly
- It provides a robust developer interface
- It allows a developer to encapsulate complex scripts directly within an SSIS project or reuse scripts across projects
- It interfaces quite well with a large number of available libraries
- SSIS memory usage can be quite high particularly when SSI and SQL server are on the same machine
- SSIS is not available on any environment other than Microsoft Windows
- SSIS does not function with any database engine back-end other than Microsoft SQL Server
December 07, 2018
SSIS for data integration and ETL!
We use SSIS to connect to API's and other DB stores/wh/marts, etc. In our projects, many different data sources and types exist, and we build BI from the disparate sources that exist within our larger clients. SSIS is used as tool to harvest those disparate sources and run jobs to populate our end DB which feeds our visualization tools.
- Source system connectivity (API's, SQL DB's, Olap Cubes, etc)
- UI which allows less technical people able to quickly and easily complete the tasks.
- Debug and quickly/easily troubleshoot logic and errors while running jobs or procedures.
- Version control sometimes seems to be an issue when many different sources are coming into play.
June 21, 2018
Good integration with MSSQL
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 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
April 06, 2018
A 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.
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.
February 15, 2018
Great ETL tool
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.
August 10, 2017
SSIS
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.
March 29, 2017
SSIS Addict
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
August 05, 2016
Use it if you have a Microsoft Stack
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.
June 03, 2016
SSIS- Mundane but Dependable
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.
May 06, 2016
A Reliable Data Preparation Tool.
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.
February 23, 2016
SSIS is ETL's best buddy for skilled SQL Developers
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?
October 27, 2015
SSIS, an ETL tool with a lot of hidden benefits!
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