Hevo vs SAP Data Services

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Our analysts compared Hevo 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

Hevo is a fully managed end-to-end data pipeline service for enterprises of all sizes. Businesses can glean proprietary insights from disparate sources that include live data from streaming devices. With its no-code interface and automated workflows, data teams can integrate business information for reporting and analytics.

It enables running minimum-impact data workflows, setting aside erroneous events and anomalous records for redressal, then assimilating them directly into the pipeline. The vendor offers a 14-day free trial while providing a few free SaaS sources to create data pipelines. Users of the Free plan have access to both free and paid sources.

Pros:
  • Cloud-based, low overhead
  • Easy-to-use interface
  • Wide range of connectors
  • Cost-effective for basic needs
  • Automated data refresh
Cons:
  • Limited customization options
  • Not ideal for complex needs
  • Scalability concerns
  • Limited data transformations
  • Limited open source integration
  • Pricing can increase with usage
  • Vendor lock-in concerns
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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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$49 Free, monthly, quote-based
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Tailored to your specific needs
$10,000 Annually
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Tailored to your specific needs
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Product Assistance

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Product Insights

  • Data Source Connectivity: Integrates with databases, SaaS systems, cloud storage, SDKs and streaming services to analyze data in multiple formats. Draws data from more than 100 sources with pre-built connectors. 
  • Deploy Seamlessly: Set up pipelines in a few minutes through a simple and interactive UI. Analyze source systems to optimize data integration calls without compromising data quality and accuracy. Replicate data utilizing minimum resources – incrementally update assets as new data comes in. 
  • Scales As Data Grows: Scales horizontally as data volumes and speed increase. Handles millions of records per minute with minimum latency, including spikes in incoming data volume. 
  • Secure Data: Protect digital assets with end-to-end encryption and two-factor authentication. The system is SOC II, GDPR and HIPAA compliant. 
  • Get Round-the-Clock Support: Reach out to vendor support for technical assistance through chat and email. 
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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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  • Data Modeling: Do more with data – create data models through a simple, visual interface and schedule to run at specific times. Ensure digital assets are always analysis-ready through materialized views within the data warehouse. 
  • Automation: Automatically manages all future data-related tasks in the pipeline – no need for ETL scripts and cron jobs. Autonomously identifies and fixes any errors detected. Ensure data flows smoothly to data repositories – detects schema changes in incoming data and replicates in destination stores. 
  • Live Monitoring: Get intelligent alerts about data sync jobs, delays and errors directly from the UI. Monitor all system logs in one place with Cloud Watch. View as data flows from sources to data warehouses. 
  • Exception Handling: Ensures no data is lost — hosts erroneous events in the replay queue and issues alerts simultaneously. Scans the replay queue for any error fixtures every few minutes, then automatically ingests the events back into the pipeline. 
  • Anomaly Detection: Spots anomalies in incoming data and notifies data teams instantly. Ensures analytics processes aren’t impacted – sets aside affected records for corrections. A fault-tolerant architecture prevents data loss in case of pipeline failures. 
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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

#28

among all
ETL Tools

#29

among all
ETL Tools

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Analyst Rating Summary

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Performance and Scalability
Metadata Management
Data Delivery
Data Sources and Targets Connectivity
Platform Capabilities
Data Delivery
Data Transformation
Performance and Scalability
Platform Capabilities
Platform Security

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Hevo
SAP Data Services
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 93 83 90 81 96 86 84 100 92 89 100 93 100 96 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Excellent User Sentiment 83 reviews
Great User Sentiment 112 reviews
94%
of users recommend this product

Hevo has a 'excellent' User Satisfaction Rating of 94% when considering 83 user reviews from 3 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.

4.7 (21)
3.9 (31)
4.67 (42)
n/a
4.8 (20)
n/a
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4.1 (54)
n/a
4.0 (27)

Awards

Hevo stands above the rest by achieving an ‘Excellent’ rating as a User Favorite.

User Favorite 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

Effortless Data Integration: Pre-built connectors and user-friendly interface simplify data extraction from diverse sources without complex coding, ideal for non-technical users.
Automated Data Pipelines: Schedule data refresh automatically and ensure timely updates in your target destination, reducing manual intervention and improving data freshness.
Cloud-Based Scalability: Serverless architecture automatically scales to accommodate growing data volumes without infrastructure management, offering flexibility and cost-efficiency.
Cost-Effective for Basic Needs: Free tier and tiered pricing plans cater to various data volumes and budgets, making Hevo an attractive option for startups and small businesses.
Actionable Data Insights: Monitoring tools and alerts provide real-time visibility into pipeline performance and data quality, enabling proactive troubleshooting and informed decision-making.
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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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Customization Constraints: While pre-built connectors are convenient, advanced data manipulation needs often require more scripting and transformation options, pushing users beyond Hevo's capabilities.
Scalability Concerns for Large Data: Handling massive datasets can lead to performance issues or limitations, particularly with complex file processing, raising concerns for organizations with rapidly growing data volumes.
Vendor Lock-in Potential: Proprietary data formats and limited open-source integration might complicate migration to other platforms in the future, making it less flexible for organizations with long-term growth plans.
Pay-as-you-go Cost Fluctuations: Unpredictable data usage can lead to unexpected charges under the pay-as-you-go model, requiring careful monitoring and potentially exceeding budget limitations.
Limited Community Support: Compared to open-source alternatives, Hevo's smaller community can offer less troubleshooting support and resource availability for specific use cases.
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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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Hevo user reviews paint a contrasting picture. Proponents praise its effortless data integration with pre-built connectors and a user-friendly interface, making it ideal for non-technical users and reducing the need for complex coding. Automated data pipelines and cloud-based scalability further attract users seeking timely data updates and flexible infrastructure. Additionally, Hevo's free tier and tiered pricing plans are lauded for being cost-effective, especially for startups and businesses with basic needs. However, critics point out limitations in Hevo's customization options. While its pre-built tools are convenient, users with complex data manipulation needs crave more flexibility and scripting options, citing challenges in tailoring pipelines for specific requirements. Scalability concerns also emerge for handling massive datasets, with some users reporting occasional performance issues. Additionally, Hevo's proprietary data format and limited open-source integration raise concerns about vendor lock-in, making it less suitable for organizations prioritizing future platform flexibility. Finally, the pay-as-you-go model can lead to unexpected costs for businesses with unpredictable data fluctuations. Compared to similar ETL tools like Fivetran or Stitch, Hevo shines in its user-friendliness and affordability. However, its limitations in customization, scalability for large data, and potential for vendor lock-in can be dealbreakers for complex ETL needs. Ultimately, Hevo excels in simplifying data integration for users with basic or moderate data volumes and budget constraints, but organizations with advanced requirements or demanding flexibility might need to explore alternative solutions.

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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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