Azure Data Factory vs Skyvia

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Our analysts compared Azure Data Factory vs Skyvia based on data from our 400+ point analysis of ETL Tools, user reviews and our own crowdsourced data from our free software selection platform.

Azure Data Factory Software Tool

Product Basics

Azure Data Factory orchestrates data movement and transformation across diverse cloud and on-premises sources. It caters to businesses struggling with data silos and complex integration needs. Key benefits include its visual interface for building ETL/ELT pipelines, native connectors to various data stores, and serverless execution for scalable data processing. User experiences highlight its ease of use, robust scheduling capabilities, and powerful data transformation tools. Compared to similar offerings, Azure Data Factory shines in its cloud-native design, integration with other Azure services, and cost-effective pay-per-use pricing based on data volume and execution duration.

Pros
  • Visual ETL/ELT builder
  • Native data store connectors
  • Serverless execution
  • Easy scheduling
  • Powerful data transformations
Cons
  • Limited custom code options
  • Steep learning curve for complex workflows
  • Potential cost increase with high data volume
  • Limited debugging options
  • Less control over serverless execution
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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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Product Insights

  • Streamlined Data Orchestration: Simplify data movement across diverse on-premises, cloud, and hybrid environments with a unified platform.
  • Boosted Developer Productivity: Leverage code-free and low-code data flows to build and manage pipelines without writing extensive scripts, saving time and resources.
  • Enhanced Scalability and Elasticity: Scale data pipelines seamlessly to handle fluctuating data volumes without infrastructure limitations, ensuring smooth performance.
  • Reduced Costs and Optimization: Pay-as-you-go pricing model and built-in optimization tools minimize infrastructure costs and maximize resource utilization.
  • Unified Data Governance: Implement consistent data security and compliance policies across all integrated data sources, ensuring data integrity and trust.
  • Accelerated Data Insights: Deliver faster and more reliable data pipelines to your analytics platforms, enabling faster time-to-insights and data-driven decision making.
  • Streamlined Data Migration: Easily migrate existing data integration workloads, including SSIS packages, to the cloud with minimal disruption and effort.
  • Rich Ecosystem of Connectors: Integrate with a vast array of on-premises and cloud data sources and applications, fostering a truly connected data landscape.
  • Enhanced Monitoring and Alerting: Gain real-time visibility into pipeline performance and proactively address potential issues with built-in monitoring and alerting features.
  • Continuous Innovation: Benefit from Microsoft's ongoing updates and enhancements to the platform, ensuring access to the latest data integration capabilities.
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  • 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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  • Data Source Connectivity: Visually integrate data sources with more than 90 pre-defined connectors through guided workflows. Connect to Amazon Redshift, Google BigQuery, HDFS, Oracle Exadata, Teradata, Salesforce, Marketo and ServiceNow, and all Azure data services. View data previews and customize as needed. 
  • Mapping Data Flow: Design code-free data transformation logic with an intuitive interface and visual tools. Schedule, control and monitor transformation tasks with easy point-and-click actions — the vendor manages code translation, path optimization and job runs at the back end. 
  • Authoring: Drag and drop to create end-to-end data processing workflows – from ingestion to reporting. Operationalize the pipeline using Apache Hive, Apache Pig, Azure HDInsight, Apache Spark and Azure Databricks. Upload data to warehouses like Azure Storage, then connect to analytics platforms for visual insights and reporting. 
  • Debugging: Debug the data pipeline as a whole or in parts — set breakpoints on specific workflows. 
  • Data Processing: Set event and schedule-based triggers to kick off the pipelines. Scales with Azure Event Grid to run event-based processing after upstream operations are complete. Speeds up ML-based pipelines and retrains processes as new data comes in. 
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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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Product Ranking

#12

among all
ETL Tools

#33

among all
ETL Tools

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Analyst Rating Summary

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Performance and Scalability
Platform Capabilities
Platform Security
Workflow Management
Data Transformation
Platform Security

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Azure Data Factory
Skyvia
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 93 92 92 96 85 100 99 84 27 65 68 16 79 71 0 25 50 75 100
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User Sentiment Summary

Great User Sentiment 128 reviews
Excellent User Sentiment 430 reviews
88%
of users recommend this product

Azure Data Factory has a 'great' User Satisfaction Rating of 88% when considering 128 user reviews from 3 recognized software review sites.

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.

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4.8 (14)
4.6 (37)
4.8 (220)
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4.8 (67)
4.4 (59)
4.8 (104)
4.2 (32)
4.8 (25)

Awards

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

User Favorite Award

Synopsis of User Ratings and Reviews

Ease of Use for ETL/ELT Tasks: Users praise the intuitive drag-and-drop interface and pre-built connectors for simplifying data movement and transformation, even for complex ETL/ELT scenarios.
Faster Time to Insights: Many users highlight the improved data pipeline efficiency leading to quicker data availability for analysis and decision-making.
Cost Savings and Optimization: Pay-as-you-go pricing and built-in optimization features are frequently mentioned as helping users keep data integration costs under control.
Reduced Development Time: Code-free and low-code capabilities are appreciated for enabling faster pipeline development and reducing reliance on coding expertise.
Improved Data Governance: Unified data security and compliance across hybrid environments are valued by users dealing with sensitive data.
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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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Limited Debugging Tools: Troubleshooting complex pipelines can be challenging due to lack of advanced debugging features and reliance on basic log analysis.
Cost Overruns: Unoptimized pipelines or unexpected usage spikes can lead to higher-than-anticipated costs in the pay-as-you-go model.
Learning Curve for Data Flows: The code-free data flow visual designer, while powerful, can have a learning curve for non-technical users, hindering adoption.
Azure Ecosystem Reliance: Integration with non-Azure services often requires workarounds or custom development, limiting flexibility.
Version Control Challenges: Lack of native version control features necessitates integration with external tools for effective pipeline management.
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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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Overall, user reviews of Azure Data Factory (ADF) paint a picture of a powerful and versatile data integration tool with both strengths and limitations. Many users praise its ease of use, particularly the drag-and-drop interface and pre-built connectors, which significantly simplify ETL/ELT tasks even for complex scenarios. This is especially valuable for reducing development time and making data pipelines accessible to users with less coding expertise. Another major advantage highlighted by users is faster time to insights. Streamlined data pipelines in ADF lead to quicker data availability for analysis, enabling data-driven decision making with minimal delay. Additionally, the pay-as-you-go pricing model and built-in optimization features are appreciated for helping users control costs. This is particularly important for organizations with fluctuating data volumes or unpredictable usage patterns. However, some limitations also emerge from user reviews. Debugging complex pipelines can be challenging due to the lack of advanced debugging tools and reliance on basic logging. This can lead to frustration and lost time when troubleshooting issues. Additionally, the learning curve for data flows, while ultimately powerful, can hinder adoption for less technical users who might prefer a more code-centric approach. Compared to similar products, ADF's strengths lie in its user-friendliness, scalability, and cost-effectiveness. Notably, its extensive library of pre-built connectors gives it an edge over some competitors in terms of out-of-the-box integration capabilities. However, other tools might offer more advanced debugging features or cater better to users with strong coding skills. Ultimately, the decision of whether ADF is the right choice depends on individual needs and priorities. For organizations looking for a user-friendly, scalable, and cost-effective data integration solution, ADF is a strong contender. However, it's essential to consider its limitations, particularly around debugging and data flow learning curve, and compare it to alternative tools to ensure the best fit for specific requirements.

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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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