The Definitive Guide to SSIS 950: Unraveling SQL Server Integration Services Package Versioning, Architecture, and Performance

1. Introduction to SSIS 950

In the intricate and data-driven world of modern enterprise IT, the seamless movement, transformation, and consolidation of data is not merely a convenience but a fundamental necessity. At the heart of countless data workflows, particularly within the Microsoft data ecosystem, lies SQL Server Integration Services (SSIS). SSIS is a powerful and versatile platform for building enterprise-level data integration and workflow solutions. However, for those who delve into its inner workings, a cryptic numerical code often emerges: SSIS 950. This number is far more than a simple identifier; it is a key that unlocks understanding of version compatibility, package structure, and the evolutionary trajectory of one of the world’s most widely used ETL (Extract, Transform, Load) tools.

What “SSIS 950” Means

At its most fundamental level, SSIS 950 refers to a specific internal version number assigned to the SSIS package format. This version number is embedded within the XML structure of every SSIS package file (with a .dtsx extension). It is used by the SSIS runtime engine, design tools like SQL Server Data Tools (SSDT) and Visual Studio, and management utilities to determine if they can correctly parse, execute, and edit a given package. The number 950 is not a marketing version like “SQL Server 2016”; it is an internal, technical schema version that signifies a specific set of capabilities, components, and a defined package structure. When a tool attempts to open a package, it checks this internal version. If the version is higher than what the tool was built to support, it will typically throw a familiar error: “The version number in the package is invalid. The version number cannot be greater than the current version.”

Why This Version Number Matters

Understanding SSIS 950 is critical for several practical reasons:

• Version Control and Team Development: In a team environment, developers may be using different versions of Visual Studio/SSDT. If one developer saves a package with a newer tool (e.g., one that creates version 1100), a colleague with an older tool (that only supports up to 950) will be unable to open it. Knowing the version mapping prevents project paralysis.

• Deployment and Execution: The SSIS runtime engine installed on a server is specific to a version of SQL Server. An SSIS 950 package is designed to run on the SQL Server 2017 or 2019 SSIS service. Attempting to run a newer package (e.g., 1200) on an older service will fail. This is a common hurdle in deployment and migration projects.

• Troubleshooting: A vast majority of common SSIS errors are related to version incompatibility. The ability to diagnose a version mismatch error by recognizing “950” saves immense amounts of time and effort.

• Upgrade Planning: When migrating an entire data estate from an older version of SQL Server to a newer one, a key task is upgrading SSIS packages. Knowing that your existing packages are version 800 (SQL Server 2014) and the target is 950 (SQL Server 2019) allows you to plan for the upgrade process, test for breaking changes, and leverage new features.

Connection to SQL Server Integration Services

SSIS 950 is not a standalone product; it is an integral part of the SSIS platform as it existed in specific releases of SQL Server. It represents the culmination of a specific era in SSIS development, encapsulating a mature set of ETL capabilities before a significant shift in deployment and management paradigms.

Relevance in ETL, Data Pipelines, and Enterprise Systems

SSIS is the workhorse for ETL and ELT processes in thousands of enterprises. An SSIS 950 package, therefore, is the executable unit of a data pipeline. It can be tasked with:

• Extracting data from heterogeneous sources like Oracle, DB2, flat files, Excel, and REST APIs.

• Transforming that data by cleaning, aggregating, merging, and applying complex business logic.

• Loading the refined data into a central repository, most commonly a data warehouse like SQL Server, or a cloud destination like Azure SQL Database or Azure Synapse Analytics.

The reliability, performance, and feature set encapsulated by the SSIS 950 version make it a cornerstone for building robust, scalable, and maintainable data integration solutions that power Business Intelligence (BI), reporting, and advanced analytics.

2. Background of SSIS Versioning

To fully appreciate the significance of SSIS 950, one must first understand the history and mechanics of SSIS versioning. Unlike the SQL Server Database Engine, which has a clear major version number (e.g., 2012, 2014, 2016), SSIS uses an internal package format version that increments, sometimes even between minor releases.

How SSIS Packages Are Versioned

When you create an SSIS project in Visual Studio/SSDT, you target a specific version of SQL Server. This target version dictates the internal package format version that will be used when you save your .dtsx files. This version number is hard-coded into the SSIS design-time and runtime components for that specific release. It is not a user-configurable setting.

Explanation of Package Format Versions

The package format version is stored in the XML of the .dtsx file. If you were to open a .dtsx file in a text editor like Notepad++, you would find an XML attribute that defines its version.

For example, a package from SQL Server 2008 would contain:
<DTS:Property DTS:Name="PackageFormatVersion">6</DTS:Property>

A package from SQL Server 2017/2019 (SSIS 950) would contain:
<DTS:Property DTS:Name="VersionPackage">8</DTS:Property>
and more specifically, the internal version is defined in the DTS:Executable XML namespace, often visible as part of the executable engine version.

The transition from a simple integer (6, 7, 8) to a more complex internal number (800, 950, 1100) occurred as the package schema became more complex.

Where the Number 950 Fits

The number 950 belongs to a lineage of version numbers that have been used since the significant architectural overhaul in SQL Server 2012. The following chart illustrates this progression:

Comparison with SSIS 1100, 1200, 1300, etc.

The jump from 950 to 1100 occurred with SQL Server 2022. This version introduced support for new data types, enhanced logging, and other minor schema changes. The key takeaway is that a higher number indicates a newer package schema. A tool designed for version 1100 can typically open a version 950 package, but the inverse is not true. The versions 1200 and 1300, as of this writing, represent future or potential internal versions for subsequent releases of SQL Server or Azure Data Factory, continuing this pattern of incremental schema evolution.

3. What Exactly Is SSIS 950?

Having placed it in context, we can now define SSIS 950 with precision.

Detailed Meaning

SSIS 950 is the internal package format version used by SQL Server 2017 and SQL Server 2019. It represents the specific XML schema, the set of available tasks and components, the API definitions, and the runtime execution semantics for SSIS packages created for and by these two SQL Server releases. It is the “language” that the SSIS runtime for SQL Server 2017/2019 understands.

When This Version Was Introduced

The 950 version was first introduced with the release of SQL Server 2017 in September 2017. It was carried forward, unchanged in its core package format, into SQL Server 2019. This means that an SSIS package created for SQL Server 2017 is binary-compatible with the SQL Server 2019 SSIS service, and vice-versa, from a package version perspective.

Which SQL Server Version It Corresponds To

As per the table above, SSIS 950 corresponds directly to:

• Microsoft SQL Server 2017 (all editions, including Developer, Standard, and Enterprise)

• Microsoft SQL Server 2019 (all editions, including Developer, Standard, and Enterprise)

Internal File Structure

An SSIS 950 package is a well-formed XML file conforming to a specific schema. The structure can be broken down into key sections:

1. Header and Metadata: Contains the package GUID, VersionGUID, CreationDate, CreatorName, and the critical VersionPackage property (which is 8 for SQL 2017/2019).

2. Connections: Defines all connection managers used by the package (e.g., OLE DB, ADO.NET, Flat File, SMTP).

3. Properties: A collection of package-level properties such as CheckpointUsage, DisableEventHandlers, Disable, and transaction isolation level.

4. Control Flow: The root container for all Control Flow tasks and containers. This includes Execute SQL Task, Data Flow Task, For Loop Container, Sequence Container, etc. Each task has its own specific properties defined within this section.

5. Data Flow (within a Data Flow Task): This is where the core ETL logic resides. It defines the Sources, Transformations, and Destinations. The specific version of the data flow components is also tied to the 950 version.

6. Event Handlers: Defines workflows that should execute in response to package events (e.g., OnError, OnPreExecute).

7. Parameters (for Project Deployment Model): A section for project and package parameters, a feature introduced in SQL Server 2012 and fully supported in 950.

Deployment Model

SSIS 950 fully supports both of the primary SSIS deployment models:

• Package Deployment Model (Legacy): This model, carried over from SQL Server 2005/2008/R2, involves deploying individual .dtsx files to the file system or to the legacy MSDB database in the SQL Server instance. Configuration is handled via XML configuration files or SQL Server tables.

• Project Deployment Model (Modern): Introduced in SQL Server 2012, this model involves deploying a single .ispac project file to the SSIS Catalog (SSISDB). This model provides superior management, monitoring, logging, and security features, including the use of Parameters and Environments. SSIS 950 packages are most commonly managed within this model in modern implementations.

4. Technical Specifications

Delving into the technical underpinnings of SSIS 950 reveals the engine that powers its ETL capabilities.

Package Architecture

An SSIS 950 package is a structured collection of executable units.

• Control Flow: The package’s orchestration layer. It consists of tasks and containers that execute sequentially or in parallel. The control flow determines the workflow of the package, not the movement of data. Key components include:

  • Data Flow Task: The most important task, which hosts the data transformation pipeline.

  • Execute SQL Task: For running SQL statements and stored procedures.

  • Execute Package Task: For modularizing work by calling other packages.

  • Script Task: For custom .NET code (C# or VB.NET) within the control flow.

  • For Loop and Foreach Loop Containers: For iterative execution.

• Data Flow: The data transformation engine, encapsulated within the Data Flow Task. This is a in-memory pipeline architecture. Key elements are:

  • Sources: Extract data from various providers (OLE DB, ADO.NET, Flat File, Excel, etc.).

  • Transformations: Modify, combine, and cleanse data (e.g., Lookup, Conditional Split, Derived Column, Sort, Merge Join).

  • Destinations: Load data into target systems.

Metadata Details

The package XML is rich with metadata. For SSIS 950, this includes references to the specific CLR (Common Language Runtime) version used by Script Tasks and Script Components (.NET Framework 4.x for SQL Server 2017/2019), the internal ID’s of all components, and lineage information for data columns that is used for debugging and data lineage tracking.

Components Supported

SSIS 950 includes a mature set of built-in components. While the core set from SQL Server 2014 (version 800) was largely retained, SQL Server 2017 and 2019 focused on improvements in other areas like scale and deployment rather than introducing a plethora of new transformations. Key components include:

• Sources: OLE DB Source, ADO.NET Source, Flat File Source, Excel Source, XML Source, ODBC Source.

• Transformations: Lookup, Conditional Split, Derived Column, Aggregate, Sort, Multicast, Merge, Merge Join, Union All, Data Conversion, etc.

• Destinations: OLE DB Destination, ADO.NET Destination, Flat File Destination, SQL Server Destination, etc.

• A significant addition in this era was the enhanced Azure Feature Pack, which provides sources and destinations for Azure Blob Storage, Azure Data Lake Store, and Azure Synapse Analytics, allowing SSIS 950 packages to operate effectively in hybrid cloud scenarios.

Upgrade/Downgrade Behavior

• Upgrade: When you open an older package (e.g., version 800 from SQL Server 2014) in SSDT for Visual Studio 2017/2019, it will detect the version mismatch and offer to upgrade the package to version 950. This process is generally one-way and irreversible. It modifies the package XML to the new schema and updates component references. It is crucial to back up packages before upgrading.

• Downgrade: There is no supported, direct way to downgrade an SSIS 950 package to an older version like 800. The only practical method is to recreate the package in the older version of SSDT/BIDS, or to manually edit the XML (a highly error-prone and unsupported practice).

5. SSIS 950 in SQL Server Versions

Understanding the exact mapping between the internal version and the SQL Server product is essential for environment management.

Which SQL Server Edition Uses SSIS 950

All editions of SQL Server that include Integration Services support the SSIS 950 package format. This includes:

• Enterprise Edition

• Standard Edition

• Developer Edition

• Evaluation Edition

The core engine and package format are identical across these editions. The differences lie in advanced features available primarily in Enterprise Edition, such as:

• Advanced data transformation sources and destinations (e.g., Change Data Capture, Data Mining components).

• The ability to scale out package execution to multiple worker nodes (a feature introduced in SQL Server 2017).

• More sophisticated logging and tuning options.

Version Mapping Chart

This expanded chart provides a clear overview of the SSIS version landscape.

Project Deployment vs Package Deployment Model

As mentioned, SSIS 950 supports both models, but the industry strongly favors the Project Deployment Model for new development.

• Package Deployment Model (Legacy):

  • Deployment Unit: Individual .dtsx files.

  • Configuration: .dtsConfig XML files.

  • Storage: File System or MSDB system database.

  • Security: SQL Server roles and Windows permissions.

  • Execution: Using DTExec.exe or DTExecUI.exe.

  • Use Case: Largely for maintaining legacy packages that have not been migrated to the project model.

• Project Deployment Model (Modern):

  • Deployment Unit: Single .ispac project file.

  • Configuration: Parameters and Environments.

  • Storage: SSIS Catalog (SSISDB) – a dedicated database.

  • Security: Integrated, role-based security within SSISDB.

  • Execution: Via stored procedures in SSISDB, SQL Agent Jobs, or DTExec.exe.

  • Use Case: All new SSIS development. Provides centralized management, logging, parameterization, and environment-specific configuration.

6. Features of SSIS 950

While the core package format version 950 itself doesn’t introduce new features, the SQL Server 2017 and 2019 releases that use it brought significant enhancements to the SSIS platform.

Performance Improvements

• Scale Out Master and Workers: This was the flagship feature for SSIS in SQL Server 2017. It allows you to distribute the execution of a single package across multiple machines (workers), managed by a central Scale Out Master. This is particularly effective for executing multiple packages in parallel or for breaking down a large, complex data flow into parallel execution paths that can be farmed out to workers, dramatically reducing ETL windows.

• Improved Azure Connectivity: The Azure Feature Pack was continuously enhanced, providing high-performance connectors to Azure data sources. The ADO.NET driver for Azure Synapse Analytics was optimized for bulk insert operations.

• In-Memory Optimizations: Continued improvements to the data flow engine’s buffer management and memory allocation led to more efficient handling of large data volumes, reducing spooling to disk.

New Components (if any)

While no major new data flow transformations were added to the core product, the SSIS Feature Pack for Azure is a critical part of the SSIS 950 ecosystem. It includes tasks and components that are effectively “new” for this version:

• Azure Blob Source/Destination: To read from and write to Azure Blob Storage.

• Azure Data Lake Store Source/Destination: For interacting with Azure Data Lake Storage Gen1.

• Azure Synapse Analytics DW Upload Task: Optimized for loading data into Azure Synapse.

• Azure HDInsight Tasks: For creating and managing HDInsight clusters and running Hive/Pig jobs.

Data Flow Engine Details

The data flow engine in SSIS 950 is a mature, in-memory pipeline. Its operation can be summarized as:

1. Source Extraction: Data is pulled from the source adapter.

2. Buffer Creation: The engine analyzes the data types and creates an in-memory buffer structure that can hold many rows of data at once.

3. Transformation Pipeline: Data flows through the transformation components row-by-row (synchronously) or in complete buffers (asynchronously). Synchronous transformations (like Derived Column) modify data in-place without requiring new buffers. Asynchronous transformations (like Sort or Aggregate) require the engine to wait for all rows to be processed before emitting new buffers, which is more memory and CPU intensive.

4. Destination Loading: The final buffers are handed to the destination adapter for insertion into the target system, typically using bulk insert methods for performance.

ETL Capabilities

SSIS 950 provides a comprehensive ETL toolkit:

• Extract: From virtually any source with a .NET or OLE DB provider.

• Transform:

  • Data Cleansing: Using Data Conversion, Derived Column, and Script Component.

  • Data Integration: Using Lookup, Merge, and Union All.

  • Data Aggregation: Using the Aggregate transformation.

  • Business Logic: Using the powerful Script Component for complex, custom .NET code.

  • Slowly Changing Dimensions (SCD): Managed via the built-in SCD Wizard.

• Load: To any supported destination with support for bulk loading, error handling, and data type mappings.

7. Common Use Cases

SSIS 950 packages are deployed to solve a wide array of data integration challenges.

Enterprise Data Migration

One of the most classic use cases. When an organization migrates from an old legacy system (e.g., an AS/400, Oracle 10g, or a set of complex Excel files) to a new ERP or CRM system, SSIS is often the tool of choice. SSIS 950 packages can be built to:

• Extract data from the heterogeneous source systems.

• Apply complex transformation logic to map the old data model to the new one.

• Handle data quality issues and de-duplication.

• Load the cleansed data into the new application’s database in a controlled, logged, and repeatable manner.

Data Warehouse Loading

This is the bread-and-butter for SSIS. A typical data warehouse ETL process built with SSIS 950 involves:

1. Staging: Using the Execute SQL Task to truncate a staging area, then using Data Flow Tasks to bulk load raw data from source systems into staging tables.

2. Dimension Processing: Using complex Data Flow Tasks to handle Type 1 and Type 2 Slowly Changing Dimensions (SCDs), looking up surrogate keys, and loading the dimension tables.

3. Fact Processing: Using Data Flow Tasks to join staged fact data with dimension tables to replace natural keys with surrogate keys, perform any necessary aggregations, and load the final fact tables.

4. Orchestration: Using a master package with Execute Package Tasks to coordinate the entire load process, ensuring dimensions are loaded before facts.

Cloud and Hybrid ETL

SSIS 950 is a cornerstone of Microsoft’s hybrid data integration story. Common patterns include:

• On-Premises to Cloud: An SSIS 950 package running on an on-premises SQL Server with the Azure Feature Pack can extract data from a local SQL Server and load it directly into Azure SQL Database, Azure Synapse Analytics, or Azure Data Lake Storage.

• Cloud to On-Premises: The reverse is also true, bringing data from cloud services down to an on-premises data mart.

• Cloud-to-Cloud: An SSIS package running on an Azure Virtual Machine (making it a fully cloud-hosted SSIS runtime) can move and transform data between different Azure services.

BI Workflows

Beyond pure ETL, SSIS is used to automate broader Business Intelligence workflows:

• Data Processing: Running the data warehouse ETL as described above.

• Cube Processing: Using the Analysis Services Processing Task to process SQL Server Analysis Services (SSAS) cubes and tabular models after the ETL is complete.

• Reporting Services Execution: Using the Script Task to call the Reporting Services web service to trigger report generation and subscriptions.

• File System Management: Using the File System Task to archive source files, move processed data files, or clean up temporary folders.

8. SSIS 950 Errors & Troubleshooting

Encountering errors is an inevitable part of working with SSIS. Many common issues are directly related to version compatibility.

“The version number in the package is invalid. The version number cannot be greater than the current version.”

This is the quintessential SSIS version error. It occurs when you try to open a package in a version of SSDT/Visual Studio that is older than the package’s internal version.

• Scenario: You try to open a package saved in SSDT for Visual Studio 2019 (version 950) in SSDT for Visual Studio 2015 (which only supports up to version 800).

• Solution: Ensure your development environment matches or exceeds the target version of the package. Install the latest SSDT for Visual Studio.

“The package is too new to be opened by this version of SSIS”

A variation of the above error, often seen when trying to execute a package.

• Scenario: You deploy an SSIS 950 package to a server running the SQL Server 2016 SSIS service. The SQL Server 2016 service does not understand the 950 format.

• Solution: Deploy the package to a server running the SQL Server 2017 or 2019 SSIS service. Alternatively, downgrade the package to version 800 in a SQL Server 2016 development environment.

Version Mismatch Issues

These can be subtle. For example, you might successfully open a package in SSDT, but a specific component (like an Azure Feature Pack component) fails to load because it was built for a different version of the .NET framework or has a different assembly version.

• Solution: Ensure all installed components (like the Azure Feature Pack, ODBC drivers, or custom script assemblies) are the correct version for your SQL Server/SSDT build.

Downgrade Problems

As stated, there is no official downgrade path. Attempting to manually edit the XML of a version 950 package to change the version number will almost certainly result in a corrupted package that cannot be opened, as the schema differences are more profound than a single number.

• Solution: The only safe solution is to recreate the package in the target, older version of SSDT.

Repairing Corrupted Packages

Packages can become corrupted due to failed upgrades, disk errors, or manual XML editing.

• Solution 1: If you use source control (which is highly recommended), simply revert to the last known good version of the package.

• Solution 2: Try opening the package in a text editor and validate the XML for well-formedness. Look for obvious errors like missing closing tags.

• Solution 3: Use the dtexec command-line utility with the /deca (dump error code address) option to get more detailed error information, which might pinpoint the corrupt section.

Visual Studio Compatibility Issues

• Scenario: You have Visual Studio 2019 installed and try to open an SSIS project originally created for SQL Server 2012. The project may fail to load or the packages may not open correctly.

• Solution: Let Visual Studio run the SSIS Project Upgrade Wizard. It will automatically convert the project file (.dtproj) to the newer format and upgrade the packages to version 950. Always back up your projects before doing this.

9. Upgrading SSIS Packages to 950 and Beyond

Migrating SSIS packages to a newer version is a critical task during a SQL Server upgrade project.

Step-by-Step Upgrade Guide

The safest and recommended method is to use the built-in upgrade wizard in SSDT.

1. Preparation:

   • Backup Everything: Ensure you have a full backup of all .dtsx packages and .dtproj files.

   • Check Source Control: Ensure all changes are committed to your source control system (e.g., Git, TFVC).

   • Document Dependencies: Note any configuration files, custom components, or external scripts.

2. Open Project in New SSDT:

   • Open Visual Studio/SSDT 2017 or 2019.

   • Go to File -> Open -> Project/Solution and select the old .dtproj file.

3. Run the SSIS Project Upgrade Wizard:

   • Visual Studio will automatically detect the version mismatch and launch the upgrade wizard.

   • The wizard will present a summary of the packages to be upgraded.

4. Review Upgrade Report:

   • After the upgrade, the wizard generates a report. Review this report meticulously.

   • It will list any components that could not be upgraded automatically, such as deprecated tasks or custom components that need to be reinstalled.

5. Validate the Upgraded Packages:

   • Open each package and check for warning icons on any tasks or components.

   • Reconfigure connection managers, especially if the server names or authentication has changed.

   • For packages using the Project Deployment Model, check that project parameters are correctly set.

6. Test Thoroughly:

   • Execute the packages in a development environment. Pay close attention to any Script Tasks or Script Components, as the .NET framework version may have changed, which could break some .NET code.

   • Validate data outputs to ensure the transformation logic still works as expected.

Backward Compatibility Rules

The SSIS runtime maintains a high degree of backward compatibility. A package built for SQL Server 2012 (version 800) will almost always run without modification on SQL Server 2019 (version 950) after it has been upgraded. The compatibility breaks are usually at the design-time level (opening in SSDT), not the runtime level, once upgraded.

Conversion Process

The conversion process modifies the package XML to the new schema (950). It updates the VersionPackage property and the DTS:Executable version references. It also updates the references to any built-in SSIS assemblies to their new versions. It does not, however, modify the logic inside Script Tasks or Script Components; that is the developer’s responsibility.

10. How SSIS 950 Works Internally

For experts and those seeking deep performance tuning, understanding the internal mechanics of the SSIS 950 engine is invaluable.

Control Flow Architecture

The control flow is a directed graph where each node is a task or container. The SSIS runtime executes this graph as follows:

1. Validation: Before execution, the package validates all tasks and connection managers. It checks for the existence of files, database connectivity, and other prerequisites.

2. Preparation: The runtime prepares each task for execution, acquiring necessary resources.

3. Execution: The runtime navigates the graph based on precedence constraints (the arrows linking tasks). These constraints can be defined on success, failure, or completion, and can include complex expressions. Tasks with no constraints between them execute in parallel, limited only by the MaxConcurrentExecutables package property.

4. Cleanup: After execution, tasks release their resources.

Data Flow Pipeline

The data flow engine is a separate, highly optimized sub-engine.

1. Buffer Creation: The engine performs a “buffer sizing” pass. It analyzes the metadata (data types, column sizes) from the source and creates an in-memory buffer layout. The default buffer size is 10MB, and the default maximum number of rows is 10,000. These can be tuned.

2. Execution Trees: The data flow path is broken down into “execution trees.” An execution tree is a segment of the data flow that can be executed by a single thread. A synchronous transformation does not break the execution tree. An asynchronous transformation does break the tree, forcing a full buffer to be produced before the next tree can begin processing. This is why asynchronous transformations are performance hotspots.

3. Thread Allocation: The data flow engine uses a thread pool to execute different execution trees in parallel where possible.

Buffer Management

Performance is dictated by efficient buffer usage.

• Buffer Spooling: If the system runs low on memory, the engine may spool buffers to disk, which is very slow. This is indicated by the BufferTempStoragePath property.

• Tuning: You can influence buffer behavior by setting the DefaultBufferSize and DefaultBufferMaxRows properties in the data flow task. Increasing the buffer size can improve performance by reducing the number of buffers that need to be allocated and processed, but it also increases memory pressure.

Transaction Handling

SSIS 950 supports distributed transactions via the Microsoft Distributed Transaction Coordinator (MSDTC).

• The TransactionOption property at the package and container level can be set to Supported, NotSupported, or Required.

• If a container’s TransactionOption is Supported and it is nested within a parent container that has started a transaction, it will join that transaction.

• This allows for atomic execution of multiple tasks; either all succeed, or all are rolled back.

11. SSIS Catalog (SSISDB) & SSIS 950

The SSIS Catalog is the central hub for managing projects in the Project Deployment Model, and SSIS 950 is fully integrated with it.

Project Deployment Model

Deploying an SSIS 950 project to the catalog is straightforward:

1. In SSDT, right-click the project and select “Deploy”.

2. The deployment process creates an .ispac file and uploads it to the specified SSISDB catalog on the target server.

3. The catalog stores the entire project, including all packages, parameters, and connection managers.

Version Management

The SSISDB catalog has built-in versioning.

• Every time you deploy a project with the same name, it creates a new version within the catalog.

• You can view all versions, see what was deployed when, and even revert to an older version if a new deployment causes issues.

Execution Logging

One of the biggest advantages of the catalog is its detailed logging.

• All package executions are logged by default.

• You can query the catalog views (e.g., catalog.executions, catalog.operation_messages) to get detailed information about package runs, including start/end times, status, and error messages.

• This provides a centralized, query-able history of all ETL activity.

Catalog Operations

You can interact with the catalog via SQL Server Management Studio (SSMS) or T-SQL.

• In SSMS, you can navigate to the Integration Services Catalogs node, right-click on a project or package, and execute it, configure parameters, and view reports.

• Via T-SQL, you can use stored procedures like catalog.create_execution, catalog.set_execution_parameter_value, and catalog.start_execution to programmatically run packages, which is ideal for scheduling via SQL Server Agent.

12. Performance Tuning for SSIS 950

A well-tuned SSIS 950 package can be orders of magnitude faster than a naive implementation.

Buffer Tuning

• Increase Buffer Size: If you have ample memory, increase the DefaultBufferSize in the data flow task from 10MB to 50MB or even 100MB. This reduces the overhead of processing many small buffers.

• Adjust Max Rows: The DefaultBufferMaxRows is a guideline, not a hard limit. The engine will create buffers that hold this number of rows unless the resulting buffer size would exceed DefaultBufferSize. Tuning this is a balance between row count and data size per row.

Parallel Execution

• Control Flow Parallelism: Design your control flow to have independent branches that can run in parallel. Ensure MaxConcurrentExecutables is set appropriately (the default is -1, meaning the number of logical processors + 2).

• Data Flow Parallelism: Within a data flow, the engine will automatically use multiple threads for different execution trees. You can aid this by minimizing the use of asynchronous transformations that create bottlenecks.

Optimization Best Practices

• Use the Fastest Source/Destination: The OLE DB destination with a “Fast Load” option is generally faster than the ADO.NET destination. The SQL Server Destination is fastest but only works when SSIS is on the same machine as the SQL Server.

• Reduce Synchronous Transformations: While they are fast, a long chain of them can be optimized. Sometimes it’s better to push logic back to the source query if possible.

• Optimize the Lookup Transformation: This is a common bottleneck.

  • Use a partial cache or no-cache mode for very large reference tables.

  • For full-cache mode, ensure the query only pulls the necessary columns.

  • Consider using a Cache Connection Manager to pre-load the lookup data.

• Avoid the OLE DB Command Transformation: This transformation executes a SQL statement for every single row, which is extremely slow. Use it only for small datasets. For large updates, stage the data and use an Execute SQL Task with a set-based update.

Memory Management

Ensure the server hosting the SSIS runtime has sufficient RAM. Monitor the Private Bytes counter for the DTExec.exe process in Performance Monitor. If you see constant paging, you need more RAM or need to reduce the memory footprint of your packages.

13. SSIS 950 vs Other Versions

A comparative analysis highlights the evolution of the platform.

940, 1100, 1200, 1300, etc.

• 940: This version does not correspond to a major public release of SQL Server. It may be an internal build number for a service pack or a specific feature pack. It is not a version you will commonly encounter.

• 950: As detailed, this is for SQL Server 2017 and 2019.

• 1100: This is the version for SQL Server 2022. Key new features include:

  • Support for UTF-8 encoded data in the data flow.

  • Parameter mapping for the Execute Package Task.

  • Enhanced logging details.

• 1200/1300: These are future versions, likely for versions of SQL Server after 2022 or for specific Azure Data Factory/SQL Server Big Data Clusters integrations. They will continue the trend of adding new data type support, connector enhancements, and cloud-focused features.

What Changes Across Versions

The changes between versions like 800, 950, and 1100 are typically:

1. XML Schema: Minor additions to the package XML schema to support new properties or components.

2. Component Versions: Updates to the internal version of built-in tasks and data flow components.

3. .NET Framework Target: The version of the .NET Framework that Script Tasks and Script Components are compiled against.

4. New Properties: Addition of new properties to existing tasks to control new behaviors.

Compatibility Charts

The golden rule is: A newer SSIS runtime/design-time can always run/open a package from an older version (after upgrade), but an older runtime/design-time cannot run/open a package from a newer version.

14. Real-World Scenarios

Example Enterprise Integration Flow: Retail Data Warehouse

A large retailer uses SSIS 950 for its nightly data warehouse refresh.

1. Master Package (Control Flow):

   • Execute SQL Task: Truncates staging tables.

   • Execute Package Task 1: Runs “PKG_Extract_Sales.dtsx” to load point-of-sale data from flat files.

   • Execute Package Task 2: Runs “PKG_Extract_Inventory.dtsx” to load inventory data from an Oracle database via an ODBC connection.

   • Execute Package Task 3: Runs “PKG_Extract_Customer.dtsx” to load new customer data from a REST API using a Script Task.

   • (The above three tasks execute in parallel).

   • Execute Package Task 4: Runs “PKG_Dim_Product.dtsx” to process the product dimension (Type 2 SCD).

   • Execute Package Task 5: Runs “PKG_Dim_Customer.dtsx” to process the customer dimension.

   • Execute Package Task 6: Runs “PKG_Fact_Sales.dtsx” to load the sales fact table, looking up the product and customer surrogate keys.

   • Analysis Services Processing Task: Processes the SSAS tabular model.

2. Data Flow Example: “PKG_Fact_Sales.dtsx”

   • Source: OLE DB Source. SQL Command: SELECT * FROM stg.Sales.

   • Lookup Transformation: Looks up ProductSK from the DimProduct table by matching the source ProductID. Configured for full cache.

   • Lookup Transformation: Looks up CustomerSK from the DimCustomer table.

   • Derived Column: Adds an AuditKey derived from a package variable.

   • OLE DB Destination: Loads into Fact.Sales using Fast Load.

Case Study: Hybrid Cloud ETL

A manufacturing company keeps its sensitive production data on-premises but uses Azure Synapse Analytics for its enterprise data warehouse and Power BI.

• Solution: They install the SQL Server 2019 Integration Services feature on a dedicated on-premises server. They develop SSIS 950 packages that:

  • Extract data from on-premises SQL Server and SAP HANA.

  • Use the Azure Feature Pack’s “Azure Synapse Analytics DW Upload Task” to efficiently push the transformed data into Azure.

  • The packages are deployed to the on-premises SSIS Catalog and scheduled via SQL Server Agent.

  • This provides a secure, managed, and high-performance pipeline from on-premises to the cloud.

15. Frequently Asked Questions

What is SSIS 950?
SSIS 950 is the internal package format version used by SQL Server Integration Services in SQL Server 2017 and SQL Server 2019. It defines the XML schema and capabilities of SSIS packages created for these versions.

How to fix version compatibility errors?
The most common error, “The version number in the package is invalid,” is fixed by ensuring your development tool (SSDT/Visual Studio) and your production SSIS service are of the same or newer version than the package you are trying to open or run. Install the latest SSDT for Visual Studio.

Which SQL Server version uses SSIS 950?
SQL Server 2017 and SQL Server 2019.

How to upgrade/downgrade packages?

• Upgrade: Open the project in a newer version of SSDT/Visual Studio and follow the Project Upgrade Wizard.

• Downgrade: There is no supported downgrade path. The package must be recreated in the older version of SSDT.

16. Glossary of Terms

• ETL (Extract, Transform, Load): A process for data integration where data is extracted from source systems, transformed to fit business needs, and loaded into a target data warehouse.

• Data Flow: The component within an SSIS Data Flow Task that handles the in-memory pipeline for moving and transforming data.

• SSISDB: The SSIS Catalog database, used for storing, managing, and running SSIS projects in the Project Deployment Model.

• Control Flow: The SSIS package element that contains the tasks and containers that define the workflow of the package.

• Integration Services: The full name of the SSIS platform, a component of Microsoft SQL Server for data integration and workflow applications.

17. Conclusion

The term SSIS 950 is a gateway into the deep technical fabric of SQL Server Integration Services. It is not an arbitrary number but a precise indicator of package format, capability, and compatibility tied directly to the powerful SQL Server 2017 and 2019 releases. For the beginner, understanding this concept is the first step in avoiding frustrating version mismatch errors. For the expert, it represents a known and stable platform upon which high-performance, scalable, and complex data integration solutions can be built, whether on-premises or in a hybrid cloud environment.

The knowledge of SSIS versioning, from 600 to 950 and beyond, is a critical skill for any data professional working in the Microsoft ecosystem. It informs development practices, deployment strategies, and troubleshooting techniques. As SQL Server continues to evolve, with SQL Server 2022 introducing version 1100, the principles surrounding these internal versions remain constant. By mastering the specifics of SSIS 950, you equip yourself to manage and modernize the data pipelines that are the lifeblood of the modern, data-driven enterprise. The future of SSIS is one of continued integration with the Azure cloud, but the foundational concepts embodied in versions like 950 will remain relevant for years to come.