SAP Data Services vs Qlik Talend Data Integration

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

Qlik Talend Data Integration Software Tool

Product Basics

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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Qlik Talend Data Integration empowers organizations to unify, govern, and integrate data from diverse sources. It shines for businesses grappling with data fragmentation and seeking to establish a trusted data foundation for analytics, AI, and informed decision-making. Key benefits include streamlined data pipelines, automated data quality checks, and real-time data synchronization. Notably, its visual drag-and-drop interface fosters ease of use, while pre-built connectors and code-free transformations accelerate development. Compared to similar tools, user experiences highlight Talend's scalability, flexibility, and robust data governance capabilities. While pricing varies based on specific needs and deployment options, expect a tiered subscription model with per-user or per-month charges.
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$10,000 Annually
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$100 Monthly
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Tailored to your specific needs
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Product Assistance

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24/7 Live Support
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24/7 Live Support

Product Insights

  • 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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  • Unified Data Foundation: Break down data silos and seamlessly integrate information from diverse sources like cloud apps, databases, and legacy systems, creating a single, trusted source for analysis and decision-making.
  • Enhanced Data Quality: Ensure data accuracy and consistency through automated cleansing, transformation, and validation processes, minimizing errors and boosting confidence in analytics.
  • Streamlined Data Pipelines: Design and automate dataflows with a drag-and-drop interface and pre-built connectors, accelerating data delivery and reducing manual tasks.
  • Real-time Insights: Gain access to up-to-date data through real-time data synchronization and event-driven triggers, enabling faster response times and agile decision-making.
  • Improved Data Governance: Implement robust data governance policies and access controls to ensure data security, compliance, and lineage tracking.
  • Increased Agility and Scalability: Respond quickly to changing business needs with a highly scalable platform that can handle growing data volumes and evolving data requirements.
  • Enhanced Collaboration: Foster collaboration across teams by providing a unified view of data and facilitating data sharing with intuitive dashboards and reports.
  • Reduced Costs and Improved Efficiency: Optimize data management processes, eliminate data silos, and reduce manual effort, leading to significant cost savings and improved operational efficiency.
  • Simplified Data Integration: Reduce the complexity of data integration with a user-friendly interface, code-free options, and pre-built components, making data accessible to users of all technical skill levels.
  • Data-Driven Decisions: Empower all levels of the organization to make informed decisions based on accurate, reliable, and readily available data, leading to improved business outcomes.
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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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  • Visual Drag-and-Drop Interface: Design and manage data pipelines with a user-friendly interface that requires minimal coding, making data accessible to users of all skill levels.
  • Pre-built Connectors: Easily connect to hundreds of data sources, including cloud applications, databases, legacy systems, and APIs, with readily available connectors.
  • Code-Free Transformations: Perform data cleansing, filtering, and manipulation through intuitive wizards and pre-built components, avoiding complex coding and accelerating development.
  • Data Quality Management: Ensure data accuracy and consistency with automated profiling, cleansing, validation, and enrichment tools, promoting trust in downstream analytics.
  • Real-time Data Synchronization: Access and synchronize data in real-time with event-driven triggers and continuous data flows, enabling immediate insights and agile decision-making.
  • Data Catalog and Lineage Tracking: Maintain a comprehensive catalog of data assets and track data lineage across transformations, fostering data transparency and governance.
  • Job Scheduling and Orchestration: Automate data pipelines through scheduling and orchestration capabilities, including dependencies and error handling, ensuring smooth data delivery.
  • Data Profiling and Monitoring: Analyze data patterns and monitor job performance with robust data profiling and monitoring tools, facilitating informed decision-making and proactive issue resolution.
  • Scalable Architecture: Handle growing data volumes and complex data pipelines with a scalable architecture that supports cloud, on-premises, and hybrid deployments.
  • Data Masking and Security: Implement data security measures, including data masking and access controls, to protect sensitive information and comply with regulations.
  • Application and API Integration: Integrate data with applications and APIs to streamline workflows and automate data exchange, fostering better decision-making within specific business processes.
  • Machine Learning and Artificial Intelligence Integration: Leverage machine learning and AI capabilities within data pipelines for tasks like anomaly detection and data enrichment, driving deeper insights and automation.
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Product Ranking

#29

among all
ETL Tools

#42

among all
ETL Tools

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Analyst Rating Summary

95
87
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84
92
92
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88
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Data Delivery
Data Transformation
Performance and Scalability
Platform Capabilities
Platform Security
Metadata Management
Performance and Scalability
Platform Capabilities
Workflow Management
Data Quality

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

SAP Data Services
Qlik Talend Data Integration
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 100 92 89 100 93 100 96 84 92 88 71 100 100 93 0 25 50 75 100
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80%
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20%
77%
23%
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85%
8%
7%
89%
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11%
89%
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11%
100%
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46%
42%
12%
80%
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90%
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

100%
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91%
9%
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91%
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9%

User Sentiment Summary

Great User Sentiment 112 reviews
Great User Sentiment 385 reviews
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.

87%
of users recommend this product

Qlik Talend Data Integration has a 'great' User Satisfaction Rating of 87% when considering 385 user reviews from 3 recognized software review sites.

3.9 (31)
4.3 (109)
n/a
4.4 (181)
4.1 (54)
4.4 (95)
4.0 (27)
n/a

Awards

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

Data Transformation Award

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Synopsis of User Ratings and Reviews

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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Ease of Use: Drag-and-drop interface and pre-built connectors make data integration accessible even for non-technical users.
Faster Data Delivery: Streamlined pipelines and automated transformations accelerate data integration processes.
Improved Data Quality: Built-in cleansing and validation tools ensure data accuracy and consistency.
Scalability and Flexibility: Handles growing data volumes and adapts to diverse data integration needs.
Strong Data Governance: Robust security features and data lineage tracking promote data privacy and compliance.
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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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Learning Curve for Advanced Features: Mastering complex transformations and customizations can require significant effort.
Performance with Large Datasets: Processing and optimizing very large datasets can be resource-intensive.
Limited Code-Free Customization: Some advanced data manipulations may necessitate manual coding for complete flexibility.
Pricing Complexity: Understanding the tiered pricing structure and potential hidden costs can be challenging.
Smaller Community Support: The user community is smaller compared to some competitors, potentially limiting available resources and peer support.
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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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Reviewing user experiences from the past year for Qlik Talend Data Integration paints a mixed picture. Many users praise its user-friendly interface, pre-built connectors, and streamlined data pipelines, making it accessible even for non-technical professionals. This ease of use, coupled with faster data delivery and improved data quality through automated cleansing, is a major draw for businesses seeking to break down data silos and gain quicker insights. However, some users highlight limitations that can be dealbreakers for complex data integration needs. Mastering advanced features and customizations can require a steep learning curve, and performance with exceptionally large datasets may necessitate optimization and resource allocation. Additionally, while code-free options are extensive, some advanced transformations may require manual coding for complete flexibility. When compared to similar products, Qlik Talend shines in its visual drag-and-drop interface and robust data governance capabilities. Users also appreciate its strong scalability and flexibility, making it adaptable to diverse data integration needs. However, some find its pricing structure complex and its community support smaller compared to competitors. Ultimately, the decision to choose Qlik Talend Data Integration hinges on individual needs and priorities. For businesses seeking a user-friendly and efficient solution for basic to moderate data integration tasks, it's a strong contender. However, those with complex data landscapes and specialized requirements may need to weigh its strengths and limitations against other options before making a final call.

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