Skyvia vs Cloud Data Fusion

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Our analysts compared Skyvia vs Cloud Data Fusion 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

Skyvia is a cloud-based data integration solution from Devart. Hosted on Azure, it has query, connect and backup capabilities. Automated workflows and a visual query wizard simplify ETL and data pipelines.

Users can set it up to accept data when a user clicks on a website or makes a selection in an application. It’s called event-based data ingestion. The vendor offers monthly subscriptions based on the volume of processed data.

  • Pros
  • Easy to use
  • Visual data pipelines
  • User-friendly interface
  • Balance of features & ease
  • Cons
  • Limited coding options
  • Fewer integrations compared to some
  • May not be ideal for complex needs
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Cloud Data Fusion streamlines data integration for businesses by building and managing pipelines that extract, transform, and load data from diverse sources. Its visual interface simplifies data movement for both technical and non-technical users, making it ideal for organizations seeking a user-friendly ETL solution. Key benefits include pre-built transformations, reusable components, and real-time data processing capabilities. Compared to other ETL offerings, users praise its intuitive design, scalability, and ease of collaboration, while acknowledging potential limitations in handling highly complex data transformations. Pricing scales with pipeline usage, offering flexibility for growing data needs.

Pros
  • Visual drag-and-drop
  • Pre-built connectors
  • Collaboration features
  • Scalable infrastructure
  • Real-time processing
Cons
  • Potential cost for large data
  • Limited custom coding
  • Learning curve for setup
  • Complex transformation challenges
  • Troubleshooting can be difficult
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Product Insights

  • Stay Competitive: Get excellent performance with high fault tolerance, thanks to the Azure cloud. It can scale by adding resources and can manage workloads efficiently.
  • Improve Decision-Making: Make informed decisions with accurate data, thanks to automatic updates, scheduled refreshes and incremental loading. Export reports to CSV files and FTP/SFTP servers.
  • Gain Timely Insights: Get accurate data from a single source of truth — a unified data store. Trust automated workflows to deliver data on time. Uncover new information with filters, joins, and string and date-time functions.
  • Act: Hit the ground running with pipeline templates or build new ones with the data flow designer. A visual query builder makes data access easy, while a code editor serves developers who want more control.
  • Secure Data: Encrypt data at rest and in motion and prepare record-wise logs for easy troubleshooting. GDPR, HIPAA and SOC compliance and access controls (MFA, SSO, RBAC) ensure that only authorized users see the necessary information.
  • Stay Connected to Data: Access from anywhere with an internet connection. It’s software-as-a-service, so it avoids the expense of on-premise infrastructure and software installation.
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  • Accelerated Time to Insights: Streamline data preparation and integration processes to quickly access, clean, and deliver actionable data for analysis, leading to faster insights and decision-making.
  • Enhanced Collaboration and Governance: Foster teamwork and maintain data quality standards with a centralized platform that enables shared pipeline creation, version control, and access management.
  • Simplified Data Integration: Empower both technical and non-technical users with a visual, code-free interface that eliminates the need for extensive programming expertise in building and managing ETL pipelines.
  • Reduced Operational Costs: Minimize infrastructure management and maintenance overhead with a fully managed cloud-based solution, allowing resources to focus on strategic data initiatives.
  • Scalability and Flexibility: Handle growing data volumes and evolving business needs seamlessly with a scalable architecture that accommodates both batch and real-time processing.
  • Enhanced Data Quality and Reliability: Implement comprehensive data validation, cleansing, and standardization processes to ensure the accuracy and integrity of data for downstream analysis and decision-making.
  • Improved Data Governance and Compliance: Enforce data security and privacy regulations with built-in controls for access management, data masking, and auditing capabilities.
  • Faster Time to Market: Accelerate the delivery of data-driven products and services by streamlining data preparation and integration, enabling quicker insights and innovation.
  • Empowered Business Users: Democratize data access and analysis by providing a user-friendly platform for self-service data exploration and integration, fostering data-driven decision-making across the organization.
  • Improved Decision Making: Gain a holistic view of business operations and make better-informed decisions based on accurate, integrated, and timely data insights.
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  • Event-Based Data Ingestion: Pull data from several sources using Skyvia Automation. Set up ingestion tasks to trigger per a schedule or after an event happens.
  • Bulk Loading: Loads large volumes or full data dumps from a source into a database. The vendor provides a Use Bulk Import checkbox with every connection popup.
  • Bidirectional Updates: Tracks the latest modifications with change data capture (CDC). It keeps data updated in both directions—from the source to the target and from the target to the source.
  • Functions: Convert data to a usable format with string and mathematical functions. The vendor provides date-time, lookup, join and filter functions. Map a single table to several related tables and create new values as desired.
  • Audit Trails: Stores logs of successfully loaded records for specific integrations and connections. It also retains records of failed integration attempts.
  • Data Encryption: Use AES 256-bit encryption to hide sensitive data at rest and when it's on the move. Additionally, the TLS protocol secures the data end-to-end.
  • Role-Based Access Control: Set up role-based users — admin, developer, member and supporter — at the workspace level. Administrators can create custom roles if they want.
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  • Visual Drag-and-Drop Interface: Build and manage data pipelines without coding, using a user-friendly interface with pre-built components for data ingestion, transformation, and loading.
  • Extensive Connector Library: Connect to a wide range of data sources, including databases, cloud storage, SaaS applications, and streaming data sources, using over 150+ pre-built connectors.
  • Pre-built Transformations: Streamline data preparation with common transformations like cleansing, filtering, joining, aggregating, and pivoting, easily applied within the visual interface.
  • Real-Time and Batch Processing: Handle both streaming data and large-scale batch processing, enabling real-time analytics and decision-making.
  • Scalable Infrastructure: Dynamically scale resources to accommodate growing data volumes and processing demands, ensuring performance and cost-effectiveness.
  • Collaboration and Version Control: Foster teamwork and maintain pipeline history with features for shared workspaces, version control, and access management.
  • Data Lineage Tracking: Track data movement and transformations throughout the pipeline, enabling data quality auditing, troubleshooting, and compliance.
  • Data Quality and Validation: Ensure data accuracy and consistency with built-in data profiling, validation, and cleansing capabilities.
  • Integration with Google Cloud: Seamlessly integrate with other Google Cloud services like BigQuery, Dataproc, Dataflow, and Cloud Storage for end-to-end data management and analytics.
  • Security and Compliance: Protect sensitive data with enterprise-grade security measures, including access controls, encryption, and auditing.
read more...

Product Ranking

#33

among all
ETL Tools

#41

among all
ETL Tools

Find out who the leaders are

Analyst Rating Summary

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93
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Platform Security
Data Delivery
Performance and Scalability
Platform Security
Data Transformation
Metadata Management

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Skyvia
Cloud Data Fusion
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 84 27 65 68 16 79 71 100 84 88 98 96 86 95 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 430 reviews
Excellent User Sentiment 139 reviews
96%
of users recommend this product

Skyvia has a 'excellent' User Satisfaction Rating of 96% when considering 430 user reviews from 5 recognized software review sites.

92%
of users recommend this product

Cloud Data Fusion has a 'excellent' User Satisfaction Rating of 92% when considering 139 user reviews from 2 recognized software review sites.

4.8 (14)
n/a
4.8 (220)
5.0 (2)
4.8 (67)
n/a
4.8 (104)
4.6 (137)
4.8 (25)
n/a

Awards

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

User Favorite Award

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

User Favorite Award

Synopsis of User Ratings and Reviews

Easy to Use: Many users praised its functionality for moving data from source to target systems and building pipelines independently.
Improved Data Integration: Users said readymade connections make it easy to pull data from cloud applications and databases.
Automated Data Workflows: Users appreciated the freedom to set up pipelines to run later. It frees them up to focus on high-level tasks.
Enhanced Data Accessibility: Users who reviewed data access said common storage gives everyone the same data to work with and avoids misdirected decisions.
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Visual Interface: Build and manage pipelines with a drag-and-drop interface, eliminating the need for extensive coding knowledge.
Scalability: Handle large and complex datasets with ease, seamlessly scaling to meet changing demands.
Integrations: Connect to a wide range of data sources and destinations, both on-premises and in the cloud.
Pre-Built Templates: Streamline development with ready-to-use templates for common ETL tasks, accelerating time to value.
Collaboration: Foster teamwork with features for sharing pipelines and managing access, promoting efficiency and knowledge transfer.
Automation: Schedule and automate pipeline execution, ensuring timely data updates and reducing manual effort.
Security: Leverage Google Cloud's robust security infrastructure for data protection and compliance.
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Limited Coding Options for Complex Transformations: While Skyvia boasts a friendly interface, complex data manipulations require coding knowledge. If teams don't know how to code, it can block them from performing deep analysis or building pipelines.
Fewer Integrations Compared to Some Competitors: It offers over 180 connectors, but if users need to connect to other sources, they might need workarounds.
May Not Be Ideal for Highly Scalable or Complex Needs: It works best with moderate data volumes, but users might need something more for large datasets and complex needs.
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Learning Curve: Interface and concepts can be initially challenging for those unfamiliar with data pipelines or Apache Beam.
Cost: Pricing model can become expensive for large-scale or complex deployments, especially with high data volumes.
Debugging: Troubleshooting pipeline errors can be difficult due to limited logging and error messages.
Customization Limits: Reliance on pre-built plugins and connectors can restrict flexibility for highly customized or niche use cases.
Performance: Some users have reported occasional performance slowdowns or job failures, especially with large datasets.
Version Control: Lacks robust built-in version control for pipelines, requiring external tools or manual management.
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Skyvia stands out for its user-friendly interface. With drag-and-drop features, anyone can connect to data sources and build pipelines, which is a big plus compared to some trickier tools that require coding.But there's a catch — the vendor keeps things simple, so it might not be the best for super complex data transformations. It has connectors for many popular apps, but some users felt the vendor should offer more options.It could be a problem for businesses that need to connect to specific data sources or want advanced functionality. Reviews also said it works great for medium data volumes.Its automatic workflows streamline data transfer and analysis while freeing workers for high-level tasks.Overall, Skyvia is a good fit for businesses that want an easy-to-use tool to integrate their data, automate tasks and gain insights without needing IT help.

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Cloud Data Fusion emerges from user reviews as a powerful ETL tool, particularly for those prioritizing ease of use and visual workflow. Its drag-and-drop interface and pre-built templates are praised for accelerating development and reducing the need for coding expertise, making it ideal for ETL beginners or teams with mixed skillsets. This accessibility shines compared to competitors like Fivetran or Stitch, which often require more technical knowledge. However, Cloud Data Fusion's user experience isn't without its bumps. Some find the learning curve steeper than expected, particularly when troubleshooting complex pipelines. Additionally, the pricing structure can become expensive for large-scale deployments, especially compared to open-source options like Airflow. For smaller teams or budget-conscious users, these drawbacks might outweigh the benefits. Where Cloud Data Fusion truly shines is its focus on collaboration and security. Features like pipeline sharing and access control promote teamwork and knowledge transfer, while leveraging Google Cloud's robust security infrastructure is a major selling point for data-sensitive organizations. This focus on collaboration and security differentiates Cloud Data Fusion from competitors, making it a compelling choice for teams working on critical data pipelines. Ultimately, Cloud Data Fusion's strengths and weaknesses paint a picture of a versatile ETL tool that excels in ease of use, collaboration, and security. While its learning curve and pricing might deter some, its user-friendly interface and focus on specific needs make it a strong contender for teams seeking a streamlined and secure ETL solution.

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