SQL Server Integration Services vs SAP Data Services

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Our analysts compared SQL Server Integration Services vs SAP Data Services based on data from our 400+ point analysis of ETL Tools, user reviews and our own crowdsourced data from our free software selection platform.

Product Basics

SQL Server Integration Services (SSIS) is a data integration tool built within Microsoft SQL Server. It excels at orchestrating data movement and transformation tasks between diverse sources and destinations, making it ideal for data warehousing, ETL (Extract, Transform, Load) processes, and database management in Windows environments. Users praise its visual workflow editor, robust data transformation capabilities, and seamless integration with other Microsoft tools. Additionally, SSIS offers built-in security features and scalability for handling large datasets. However, its reliance on the Microsoft ecosystem, limited open-source compatibility, and potentially complex learning curve can be drawbacks. Pricing is part of the SQL Server license, ranging from affordable Express editions to more expensive Enterprise versions depending on user needs and server configurations. Overall, SSIS is a powerful and cost-effective option for organizations heavily invested in the Microsoft suite and primarily focused on Windows server environments. For those seeking open-source flexibility or broader platform compatibility, alternative data integration tools may be worth exploring.

Pros:
  • Visual workflow
  • Strong data transformations
  • Microsoft integration
  • Built-in security
  • Scalable for large volumes
Cons:
  • Windows only
  • Limited open source
  • Steep learning curve
  • Pricing with SQL Server
  • Closed-source ecosystem
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Formerly known as BusinessObjects Data Services (BODS), it’s part of the information management layer of SAP’s Business Technology Platform. With a focus on data quality, it extracts, transforms and loads all data types to enterprise interfaces.

Dashboards enable visual analytics and display the impact of data quality issues on downstream workflows. Auto documentation allows teams to write dataflow information and add comments for collaboration. An intuitive UI and Unicode compliance provide localization across more than 190 countries. Data security is ensured with AES 128-bit encryption.

Pros:
  • Robust transformations
  • Scalable for large volumes
  • Tight SAP integration
  • Visual job design
  • Centralized governance
Cons:
  • High cost and licensing
  • Steep learning curve
  • Limited open source
  • SAP ecosystem dependence
  • Complex job maintenance
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$300 Monthly
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$10,000 Annually
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Tailored to your specific needs
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Product Assistance

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Product Insights

  • Maximize ROI: Performs complex transformations without needing a staging area. Persists data temporarily to a native raw format file using the file system. 
  • Connect to Data Sources: Draws data from Microsoft SQL Server, IBM DB2, Oracle, HP Vertica, MySQL, MongoDB and OData. Pull data from repositories that can’t be sourced directly like FTP, HTTP, MSMQ, Analysis Services and Server Management Objects (SMO). 
  • Integrate with SAP Products: Natively accesses the application model and relevant metadata in SAP Business Suite offerings. Reads data based on programming languages such as ABAP, IDocs, BAPI, RFC and SAP extractors. 
  • Extend As Needed: Write code to define connection objects, log providers, transforms and tasks. 
  • Maintain Data Quality: Handles data from heterogeneous data sources within the same package. Monitor errors through a variety of logging and auditing options. 
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  • Maximize ROI: Streamline processes and maximize efficiency. Access data where it’s stored, load and move it while ensuring optimal speed and performance. Unlock contextual insights by transforming data. 
  • Source Disparate Data: Draws data from files, XML, relational databases, web services and mainframes. Connects to big data, cloud and NoSQL systems including Amazon Web Services, Google Cloud Platform, Microsoft Azure Marketplace, SAP Cloud Platform, Vertica, MongoDB, Apache Spark on Apache Hive, Teradata and Hadoop. Aggregates unstructured data like text from Adobe PDFs, Microsoft Word, Outlook, Excel and more. 
  • Deploy Anywhere: Implement on-premise, in the cloud or go hybrid. Move existing content and assets to and from SAP Data Intelligence Cloud and use them across the enterprise. 
  • Permissions Management: Uses the Central Management Server (CMS) for users’ accounts and permissions management. Add and remove team members’ rights and manage access to repositories on a per individual basis. 
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  • Big Data Support: Connects to new, in-demand big data sources like databases, systems, files and unstructured content. Access mainframe sources and captured data changes in real time. Expand cloud support for big data with Microsoft Azure, Impala, Cassandra, OData and Apache Hive.
  • Import/Export Wizard: Move data from a variety of source types to disparate destination types, including text files and other SQL Server instances. Create packages that move data across systems seamlessly, without transformations. 
  • Build Integration Packages: Create and maintain integration packages through the SSIS Designer. Deploy the package and view the execution status at run time. Add functionality to packages through dialog boxes and windows. Configure the development environment through SQL Server Data Tools (SSDT). 
  • Built-in Data Transformations: Provides aggregation, pivot, unpivot, cache transform, fuzzy lookup, data conversion, data mining query and partition processing. Leverage a wide range of transform capabilities like fuzzy logic, data profiling, data and text mining and direct insert to SSAS. 
  • Secure Business Data: Provides threat and vulnerability mitigation, and access control. Sign packages with digital certificates that ensure customers open and run packages only from trusted sources. 
  • Precedence Constraints: Control task runs by defining precedence constraints. Connect tasks to control the workflow and configure to work based on an SSIS expression or the status of the preceding job. 
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  • Optimize Performance: Pushes down entire processing workflows into the source or target system for the best throughput. Partitions the data and processes it in parallel, fully independent streams. 
  • Process Unstructured Data: Reveal data relationships and interactions – the who, what, when and how of text. Unlock unstructured text data insights through natural-language processing. Understand the meaning and context of information, not just the words. 
  • Merge Datasets: Merges multiple incoming datasets into one output entity with the same schema as the incoming dataset. Performs the SQL UNION ALL operation through merge transform. 
  • Maintain Data Quality: Gain employees’ and clients’ trust with reliable, accurate, unique data. Enforce data quality standards in real time and perform quality checks before analyzing and integrating data. Embed data duplication checks into workflows and systems. See beyond errors and inconsistencies to uncover a single version of the truth. 
    • Data Profiling: Cleanse and standardize data like names, addresses, emails, phone numbers and dates. Ensure consistency of key reference data used across the organization. 
    • Master Data Management: Integrates with SAP NetWeaver MDM to provide more cleansing and matching capabilities. 
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Product Ranking

#8

among all
ETL Tools

#29

among all
ETL Tools

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Analyst Rating Summary

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Data Quality
Data Transformation
Platform Security
Metadata Management
Workflow Management
Data Delivery
Data Transformation
Performance and Scalability
Platform Capabilities
Platform Security

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

SQL Server Integration Services
SAP Data Services
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 88 100 76 100 93 0 91 100 92 89 100 93 100 96 0 25 50 75 100
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we're gathering data
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

we're gathering data
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User Sentiment Summary

Great User Sentiment 503 reviews
Great User Sentiment 112 reviews
84%
of users recommend this product

SQL Server Integration Services has a 'great' User Satisfaction Rating of 84% when considering 503 user reviews from 2 recognized software review sites.

80%
of users recommend this product

SAP Data Services has a 'great' User Satisfaction Rating of 80% when considering 112 user reviews from 3 recognized software review sites.

n/a
3.9 (31)
4.3 (279)
4.1 (54)
4.1 (224)
4.0 (27)

Awards

SelectHub research analysts have evaluated SQL Server Integration Services and concluded it earns best-in-class honors for Data Transformation.

Data Transformation Award

SelectHub research analysts have evaluated SAP Data Services and concluded it earns best-in-class honors for Data Transformation.

Data Transformation Award

Synopsis of User Ratings and Reviews

Visual Workflow: Drag-and-drop interface simplifies complex data flows, making integration tasks intuitive and manageable, even for users without extensive coding experience.
Robust Data Transformations: Cleanses, transforms, and validates data to ensure accuracy and consistency before integration, improving data quality and trust in downstream analytics.
Microsoft Integration: Seamlessly integrates with other Microsoft tools and platforms like SQL Server and Azure, streamlining data workflows within existing infrastructure and reducing the need for additional software.
Scalability and Performance: Handles large datasets efficiently with parallel processing and optimization techniques, minimizing processing time and ensuring smooth data integration for growing data volumes.
Built-in Security: Supports encryption, data masking, and role-based access controls for secure data handling and compliance with industry regulations, providing peace of mind and reducing security risks.
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Robust Data Transformations: Handles complex data cleansing, manipulation, and enrichment tasks with a wide range of built-in functions, ensuring data quality and accuracy for downstream analytics.
Tight SAP Integration: Seamlessly connects and transforms data within the SAP ecosystem, simplifying data flows and reducing integration complexity for SAP-centric organizations.
Scalable for Large Volumes: Efficiently handles high data volumes with parallel processing, data partitioning, and optimization techniques, ensuring smooth performance for growing data needs.
Visual Job Design: Intuitive drag-and-drop interface simplifies job creation and maintenance, making data integration accessible even for users with less technical expertise.
Centralized Governance: Provides centralized control and monitoring of data flows, ensuring data consistency, lineage tracking, and adherence to compliance regulations.
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Limited Open Source: Relies heavily on Microsoft technologies and lacks extensive open-source integrations, potentially restricting customization and community support compared to more open platforms.
Steep Learning Curve: While the visual interface is helpful, mastering complex data flows and transformations can require significant training and experience, especially for users unfamiliar with the platform.
Windows Only: Limited to Windows environments, excluding non-Microsoft operating systems like Linux or macOS, hindering platform flexibility and potentially requiring additional infrastructure investment.
Closed-Source Ecosystem: Limited transparency into internal algorithms and processes can make troubleshooting and debugging complex issues challenging, requiring specialized knowledge or relying on Microsoft support.
Cost Tied to SQL Server: Pricing depends on the chosen SQL Server edition, potentially increasing costs for organizations already invested in other database solutions or needing only basic data integration functionalities.
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High Cost and Licensing: Requires separate licensing fees on top of existing SAP licenses, with costs scaling based on features, user licenses, and deployment options. Can be expensive compared to open-source or alternative data integration tools.
Steep Learning Curve: Mastering the visual job design and complex data transformations can require significant training and experience, especially for users unfamiliar with the platform.
Limited Open Source: Relies heavily on proprietary SAP technologies and lacks extensive open-source integrations, potentially restricting customization and community support compared to more open platforms.
SAP Ecosystem Dependence: Tight integration with the SAP ecosystem can limit flexibility and increase costs for organizations using other data sources or platforms.
Complex Job Maintenance: Managing and maintaining complex data flows with numerous transformations and dependencies can be challenging, requiring specialized expertise.
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User reviews of SQL Server Integration Services paint a contrasting picture. Proponents praise its intuitive visual workflow, robust data transformation capabilities, and seamless integration with the Microsoft ecosystem. This makes it ideal for organizations already invested in Microsoft tools and requiring efficient data movement within Windows environments. The built-in security features and scalability for handling large datasets are further pluses, offering peace of mind and ensuring smooth performance for growing data volumes. However, critics point to its heavy reliance on Microsoft technologies and limited open-source compatibility as major drawbacks. This can restrict customization and community support compared to more open platforms like Talend or Apache Airflow. The steep learning curve and Windows-only limitation can also be hurdles, requiring dedicated training and potentially hindering platform flexibility. Additionally, the closed-source nature can make troubleshooting complex issues challenging. Finally, pricing tied to SQL Server editions may not be cost-effective for organizations needing only basic data integration functionalities or using other database solutions. Ultimately, SQL Server Integration Services shines for its robust data handling, intuitiveness, and Microsoft integration within Windows environments. However, its limited open-source compatibility, steep learning curve, and reliance on SQL Server licensing make it less ideal for organizations seeking greater flexibility, affordability, or platform independence. Carefully weighing your specific needs and resources against its strengths and limitations is crucial before choosing SSIS for your data integration needs.

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User reviews of SAP Data Services paint a contrasting picture. Proponents praise its robust data transformations, seamless SAP integration, and scalability for handling large data volumes. The visual job design and centralized governance features further attract organizations needing intuitive data flow creation and efficient data lineage management. Additionally, SAP Data Services shines in SAP-centric environments, simplifying data movement within existing infrastructure. However, critics point to its high cost and complex licensing as major drawbacks, making it less compelling for organizations on a budget or using diverse data sources. The steep learning curve and limited open-source compatibility can also be hurdles, requiring dedicated training and potentially restricting customization options. Compared to open-source alternatives like Talend or Apache Airflow, SAP Data Services offers less flexibility and community support. Additionally, its tight dependence on the SAP ecosystem can add complexities and raise costs for organizations not fully invested in SAP solutions. Ultimately, SAP Data Services excels in data transformation, scalability, and seamless SAP integration, making it a powerful choice for SAP-centric organizations with complex data needs and the resources to invest in its capabilities. However, its high cost, limited open source, and SAP dependence make it less suitable for budget-conscious organizations or those seeking greater platform flexibility and broader community support.

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