Fivetran vs Cloud Data Fusion

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Our analysts compared Fivetran 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

Fivetran is a cloud-native data extraction tool that simplifies and streamlines the data analysis process with a zero-maintenance pipeline that ensures expedient, transparent delivery of data from source to warehouse. Built to empower analysts, it allows users to accelerate analytics and achieve faster time-to-insights without the need for complex engineering, promoting more efficient data-driven decision-making for users of all technical skill levels.

Suitable for small to large companies, it is a public-cloud hosted SaaS available through annual subscriptions, paid via invoice. Pricing is volume based with three tiers of plans, in ascending order of offerings and cost: Starter, Standard and Enterprise.

Pros
  • Easy to use interface
  • Connects to many data sources
  • Fast and reliable data pipelines
  • Centralized data management
  • Scalable for large data volumes
Cons
  • Limited customizability
  • Can be expensive for complex needs
  • Not ideal for real-time data
  • Limited support for data transformations
  • Learning curve for advanced features
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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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$55 Monthly
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Product Insights

  • Five-Minute Setup: The platform boasts a zero-maintenance configuration process that can have users up and running in 10 clicks.
  • Data Simplified: Users can simplify their data stack with streamlined data extraction and preparation processes, allowing for more accurate and efficient access to analytics.
  • Optimized Loading: Automatic updates reduce data entry tasks and ensure real-time accuracy across storage facilities. The platform also reduces workloads on cloud data warehouses by putting the brunt of demand on their servers instead of the warehouses’. 
  • Centralize Data: The solution helps users to extract data from disparate sources and load it into their data warehouse to create a single, cohesive source of truth in the cloud.
  • Flexibility: Standing apart from many traditional data tools, Fivetran utilizes ELT (extract, load, transform) over ETL (extract, transform and load). By flipping the last two steps of the process and postponing data transformation, it ensures that stored data won’t be compromised by transformations, allowing users to perform analysis more deliberately and securely.
  • Smooth Integrations: Integration with other systems is intuitive and smooth with this platform. Its seamless data sync allows users to draw data from their CRM, ERP or other business solutions as well as a range of cloud data sources, allowing for real-time monitoring.
  • Data Security: The system has advanced security features and is compliant with PCI, HIPAA, GDPR and SOC 2 standards. It also encrypts data in motion and at rest, purging data after every sync. 
  • Built to Scale: The platform helps users navigate a world of exponential data growth, with instantly scalable cloud resources, optimized processes and pricing plans that keep up with companies as they grow. 
  • Free Trial: Interested buyers can receive a free 14-day trial of the platform to test connectors and features by signing up on the vendor’s website. Users can add up to two sources and set up an unlimited number of connectors for those sources, pointing to one destination. Users interested in adding more sources or destinations can contact the Fivetran sales team for more information.
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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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  • Data Connectivity: The solution has data connectors for 100 sources, with the option for users to create their own data connector to APIs not yet natively supported. It directly pulls information from cloud applications. Users can also upload or email files into a cloud storage service and have that data loaded into their warehouse. The system reflects changes made to live files such as Google Sheets.
  • Extract Data: The solution connects natively to over 100 SaaS sources, automatically extracting information from those sources after an admin has granted the tool access through OAuth. The system normalizes, cleanses and standardizes data before loading.
  • Data Sync: Upon connection, the system performs a historical sync. From there, instead of arduously reloading full data dumps from APIs and databases, the solution optimizes loadings by incrementally updating data sources in batches, with data load time configurable as frequently as five minutes and as infrequent as every 24 hours.
  • Load into Cloud Data Warehouses: Fivetran supports modem cloud warehouses like BigQuery, Snowflake, Azure and Redshift.
  • Transform Data: The platform preps data, normalizing schemas from APIs, so that it can be analyzed instantly. Transformations always happen in the warehouse so that the raw data is always available alongside the transformed data; data will never be lost and the transformations can be edited and run again on the raw data.
  • Alerts: The system notifies users if there are delays or issues in any step of the process.
  • Dashboards: Users interact with the platform via dashboards that display information about ELT processes in a visual, easy-to-digest format.
  • System Logs: The solution maintains transparency with granular system logs of every sync that users can cross-reference in their own logging system.
  • Metadata Management: A suite of policies and procedures allows users to manage the data which describes other data such as file size, date of data creation, tags, titles, authors, etc.
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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.
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Product Ranking

#7

among all
ETL Tools

#41

among all
ETL Tools

Find out who the leaders are

Analyst Rating Summary

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

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Fivetran
Cloud Data Fusion
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 86 75 93 94 96 100 81 100 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 28 reviews
Excellent User Sentiment 139 reviews
92%
of users recommend this product

Fivetran has a 'excellent' User Satisfaction Rating of 92% when considering 28 user reviews from 2 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.

n/a
5.0 (2)
4.64 (14)
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4.6 (14)
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4.6 (137)

Awards

Fivetran 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

Effortless Data Integration: Connects to hundreds of data sources with pre-built connectors and minimal setup.
Automated Data Pipelines: Schedules and runs data transfers reliably, freeing up time for analysis.
Centralized Data Management: Provides a single source of truth for all your data, simplifying reporting and decision-making.
Scalable for Growth: Handles large data volumes with ease, adapting to your evolving needs.
Improved Data Visibility: Makes data readily available for everyone in your organization, fostering data-driven decision-making.
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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 Customizability: Relies on pre-built connectors, making complex data pipelines or transformations challenging.
Costly for Advanced Needs: Pricing scales with data volume and complexity, becoming expensive for intricate ETL processes.
Batch-Oriented Transfers: Focuses on scheduled data refreshes, not ideal for real-time needs or low-latency pipelines.
Basic Data Transformations: Offers limited built-in transformations, requiring additional tools for complex data manipulation.
Advanced Feature Learning Curve: Mastering custom connectors, scripting, or other advanced features requires technical expertise.
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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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Users praise Fivetran for its ease of use and effortless data integration. "Setting up connectors is straightforward," one reviewer comments, "like plugging in appliances." This plug-and-play simplicity sets it apart from competitors like Stitch, often lauded for its flexibility but criticized for a steeper learning curve. However, Fivetran's strength in pre-built connectors comes at a cost: limited customizability. While users love its "seamless data movement," another user points out it's "not ideal for complex transformations," requiring additional tools that negate its initial ease. This lack of advanced ETL capabilities puts it behind platforms like Informatica PowerCenter, but at a fraction of the cost. Ultimately, Fivetran shines for its user-friendly approach and reliable data pipelines, perfect for businesses prioritizing simplicity and scalability. But for complex data manipulation or real-time needs, users might find themselves yearning for the power and flexibility of other ETL solutions.

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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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Screenshots

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