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Why You Should NOT Use SSIS in 2023

In the ever-evolving world of data integration and transformation, tools and technologies are constantly being assessed for their relevance and efficiency. SQL Server Integration Services (SSIS) has been a staple in the Microsoft data ecosystem for years, but as we step into 2023, there are compelling reasons to reconsider its use.

Key Takeaways:

  • SSIS is becoming outdated with the rise of modern ETL tools.
  • There are performance and scalability concerns.
  • The learning curve for SSIS can be steep compared to newer tools.
  • Cloud-native solutions are becoming the norm, and SSIS might not fit well in this paradigm.

Of course there are many reasons why you SHOULD use SSIS in 2023. We have an article here to offer a counter-balance to this one!

The Rise of Modern ETL Tools

With the advent of cloud-native solutions and the increasing need for real-time data processing, traditional ETL tools like SSIS are facing stiff competition. Newer tools offer more flexibility, scalability, and are often more cost-effective.

  • Scalability Concerns: SSIS, being a product of its time, wasn’t designed with the massive scalability requirements of today’s data operations in mind. Modern ETL tools are built to handle vast amounts of data seamlessly.
  • Performance Issues: As data volumes grow, performance becomes a critical concern. SSIS can struggle with very large datasets, especially when complex transformations are involved.

Steep Learning Curve

For newcomers to the data integration world, SSIS can be daunting. Its interface, while powerful, is not as intuitive as some of the newer tools on the market.

  • Complexity: While SSIS is undoubtedly powerful, that power comes with complexity. This can be off-putting for new users and can slow down development times.
  • Documentation: Although there’s a wealth of information available, finding the right resources can be a challenge. Newer tools often have more streamlined and user-friendly documentation.

Cloud-Native is the Future

As companies move more and more of their operations to the cloud, tools that are not cloud-native or have limited cloud capabilities will struggle to remain relevant.

  • Integration with Other Cloud Services: Modern ETL tools are often designed to integrate seamlessly with other cloud services, making it easier to build end-to-end data pipelines.
  • Cost: Running SSIS, especially in a cloud environment, can be more expensive than using a cloud-native ETL tool.

SSIS vs Azure Data Factory

SSIS in 2023: Is It Really Going Away?

While it’s clear that there are challenges associated with SSIS in the modern data landscape, it’s also worth noting that many organizations still rely on it. This is often due to legacy systems, existing expertise, or specific use cases where SSIS shines.

  • Legacy Systems: Many organizations have significant investments in SSIS, both in terms of developed packages and expertise. Migrating away from SSIS can be a major undertaking.
  • Specific Use Cases: There are scenarios where SSIS might still be the best tool for the job, especially in hybrid environments where on-premises data sources need to be integrated with cloud services.

External Perspectives

The data community has diverse opinions on the relevance of SSIS in 2023. Some believe it’s a dying technology, while others see its value in specific scenarios. For a broader perspective, consider these external discussions:

Exploring the Alternatives

As the limitations of SSIS become more apparent in the current data landscape, many organizations are looking for alternatives. Here are some of the top contenders that have emerged as viable replacements for SSIS in 2023:

Azure Data Factory

Microsoft’s own Azure Data Factory has been gaining traction as a cloud-based ETL service. It offers:

  • Seamless integration with other Azure services.
  • Code-free visual environment for ETL and ELT processes.
  • Over 80 natively built connectors.

Read about Azure Data Factory here: What is Azure Data Factory?

Talend Open Studio

Talend Open Studio is an open-source integration software that offers:

  • A platform to build basic data pipelines.
  • Graphical profiles of data.
  • Local installation with an open-source environment.


Skyvia is a cloud platform that provides:

  • No-coding data integration (both ELT and ETL).
  • Workflow automation.
  • Support for major cloud apps and databases.

Read more: List of Best SSIS Alternatives & Competitors 2023

The Shift to Real-time Data Processing

With the increasing demand for real-time analytics, tools that can’t process data in real-time are falling behind. SSIS, primarily designed for batch processing, struggles to meet these real-time requirements.

  • Latency Issues: SSIS can introduce latency, especially when dealing with large datasets.
  • Lack of Native Streaming Support: While there are workarounds to enable streaming in SSIS, they can be complex and not as efficient as tools designed for streaming.

More info:

SSIS in 2023: Community and Support

One of the significant advantages of newer tools is the active community and robust support they offer. This is especially important as the pace of change in the data world is rapid, and having a community to lean on can be invaluable.

  • Active Forums and Discussions: Newer tools often have active forums where users can ask questions, share knowledge, and help each other out.
  • Regular Updates and Patches: With an active community and support, newer tools tend to receive regular updates, ensuring they stay relevant and secure.

Check out these SSIS community resources:

SSIS Cost Implications

While SSIS comes as part of the SQL Server license, there are hidden costs associated with its use, especially when scaling or integrating with cloud services.

  • Scaling Costs: As data volumes grow, scaling SSIS can become expensive, especially if additional hardware or virtual machines are required.
  • Integration Costs: Integrating SSIS with cloud services or other modern tools can introduce additional costs, both in terms of money and development time.