Fivetran vs InfoSphere Information Server

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Our analysts compared Fivetran vs InfoSphere Information Server 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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InfoSphere Information Server is a data integration powerhouse designed to unify information across complex, diverse systems. It excels at extracting, transforming, and loading data (ETL/ELT) for tasks like building data warehouses, powering analytics, and driving business insights. Best suited for large enterprises with demanding data needs and dedicated IT resources, InfoSphere boasts robust features like comprehensive data source/target connectors, powerful transformation tools, and advanced governance capabilities. User feedback highlights its scalability, security, and job automation as key benefits. However, its complexity and steep learning curve can be daunting for smaller setups. Additionally, the high licensing costs and resource-intensive nature might dissuade budget-conscious organizations. Compared to other data integration tools, InfoSphere leans towards high-volume, mission-critical scenarios, while alternative options might offer simpler setups or cater to broader use cases. Choosing the right fit depends on individual needs and priorities. Ultimately, InfoSphere Information Server shines when organizations need a robust, feature-rich platform to conquer complex data challenges, even at the cost of increased upfront investment and initial learning hurdles.

Pros
  • Powerful ETL & ELT capabilities
  • Wide range of data sources & targets
  • Job scheduling & monitoring
  • Data quality & transformation tools
  • Scalable & secure architecture
Cons
  • Steep learning curve & complexity
  • High licensing costs
  • Limited out-of-the-box connectors
  • Performance bottlenecks with large datasets
  • Resource-intensive for deployment & maintenance
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$55 Monthly
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$20,000 Annually
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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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  • Unified Data Landscape: Break down data silos and seamlessly integrate information from diverse sources, including databases, applications, and cloud platforms, providing a holistic view for improved decision-making.
  • Enhanced Data Quality: Ensure data accuracy and consistency through powerful cleansing, standardization, and transformation tools, minimizing errors and boosting trust in your data assets.
  • Streamlined Data Movement: Automate and orchestrate data movement using flexible ETL/ELT workflows, speeding up data delivery and reducing manual effort for critical business processes.
  • Powerful Data Transformation: Manipulate and enrich data to meet specific needs through a comprehensive set of transformation functions, unlocking its full potential for analytics and reporting.
  • Scalable and Secure Architecture: Handle large data volumes and complex integrations with confidence thanks to a robust and secure architecture, ensuring uninterrupted data flow and safeguarding sensitive information.
  • Improved Operational Efficiency: Automate routine data tasks, reduce IT workload, and optimize resource utilization, freeing up staff and resources for higher-value activities.
  • Enhanced Data Governance: Implement data governance policies and ensure compliance with regulations through features like lineage tracking and access controls, fostering data transparency and responsible usage.
  • Greater Business Agility: Respond rapidly to changing data needs and support new initiatives with agile data integration capabilities, empowering faster time-to-market and increased business flexibility.
  • Improved Collaboration and Decision-Making: Foster greater collaboration across teams by providing everyone with access to reliable and consistent data, leading to better informed decisions and data-driven strategies.
  • Reduced Integration Costs: Streamline data management processes, eliminate data redundancies, and optimize infrastructure usage by consolidating data integration needs into a single platform, potentially leading to cost savings.
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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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  • Data Integration: Collect, transform and share large amounts of complex data assets across the organization. Reduce development time, and scale flexibly by leveraging built-in data transformation functions. Deliver data in real time to business applications in bulk, virtually or through change data capture (CDC). 
  • Data Quality: Cleanse and validate data — in batches and real time — then load it into analytical views for consistent monitoring. Establish data quality metrics across the organization by reusing these data views. Ensure consistent information organization-wide by linking related records across systems. 
    • Business Glossary: Create a single source of truth – consolidate disparate data into unique, reliable records and load into repositories and master data applications. Share insights with confidence powered by complete access to proof of lineage and data quality. A centralized hub maintains data governance rules. 
  • Information Governance Catalog: Empower data scientists and analysts to explore and analyze business data in compliance with enterprise governance standards. Create, manage and share a common business language, design and apply rules and track data lineage. Extend on-premise governance investment to the cloud by integrating with IBM Watson Knowledge Catalog. 
  • Metadata Repository: Share imported metadata and other assets in any server component across. the organization. Stores project configurations, reports and results for all the server’s components in one unified repository 
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Product Ranking

#7

among all
ETL Tools

#32

among all
ETL Tools

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Analyst Rating Summary

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Platform Capabilities
Platform Security
Metadata Management
Data Transformation
Data Sources and Targets Connectivity
Data Delivery
Metadata Management
Platform Security
Workflow Management
Data Quality

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Fivetran
InfoSphere Information Server
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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 99 94 95 100 0 100 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
Good User Sentiment 80 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.

77%
of users recommend this product

InfoSphere Information Server has a 'good' User Satisfaction Rating of 77% when considering 80 user reviews from 3 recognized software review sites.

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4.0 (21)
4.64 (14)
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4.6 (14)
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4.6 (27)
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3.1 (32)

Awards

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

User Favorite Award

SelectHub research analysts have evaluated InfoSphere Information Server and concluded it earns best-in-class honors for Workflow Management.

Workflow Management 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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Powerful Data Handling: Handles complex ETL/ELT processes and diverse data sources (relational, flat files, cloud platforms) with ease, streamlining data movement and integration.
Enhanced Data Quality: Ensures data accuracy and consistency through robust cleansing, validation, and transformation tools, boosting trust and reliability in data insights.
Scalability and Security: Supports large data volumes and complex integrations with confidence, safeguarding sensitive information through granular access controls and encryption.
Job Automation and Monitoring: Automates data pipelines and workflows, reducing manual effort and simplifying task management with comprehensive monitoring capabilities.
Improved Operational Efficiency: Centralizes data integration processes, eliminates data silos, and frees up IT resources for higher-value tasks, leading to cost savings and increased productivity.
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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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Steep Learning Curve: Complex interface and feature-rich platform require significant training and expertise, even for experienced data professionals.
High Cost of Ownership: Licensing fees, maintenance, and potential hardware/infrastructure upgrades can make it a costly solution for smaller organizations or simpler data needs.
Limited Out-of-the-Box Connectors: May require custom development or third-party tools for integration with certain data sources or applications, increasing implementation complexity and costs.
Performance Bottlenecks: Can experience slowdowns or scalability issues with very large datasets or intricate ETL/ELT processes, demanding careful optimization and resource allocation.
Limited Cloud-Native Functionality: Core features are primarily designed for on-premises deployments, with cloud options requiring additional setup and configuration, potentially hindering agility and flexibility.
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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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User reviews of InfoSphere Information Server paint a picture of a powerful data integration tool, capable of handling complex tasks and diverse data sources. Admiration for its robust ETL/ELT capabilities, data quality tools, and secure architecture echoes frequently, with users citing improved data accuracy and streamlined data movement as major benefits. Automation features and job monitoring are also praised for boosting operational efficiency and freeing up resources. However, the praise comes with caveats. The steep learning curve and demanding resource requirements are consistent gripes, making InfoSphere a better fit for larger organizations with dedicated IT expertise and infrastructure. The high cost of ownership, including licensing, maintenance, and potential hardware upgrades, further strengthens this point. Additionally, the limited out-of-the-box connectors and potential performance bottlenecks with massive datasets are concerns for some users. Compared to competitors, InfoSphere shines in its scalability and security, catering to high-volume, mission-critical scenarios. However, users also acknowledge the presence of simpler, more user-friendly options that might be better suited for smaller setups or less complex data needs. Ultimately, the choice boils down to individual priorities. If data volume, security, and advanced features are paramount, InfoSphere stands out, despite its demanding nature. But for those seeking a smoother learning curve or broader use cases, other solutions might offer a better fit. In essence, user reviews reveal InfoSphere Information Server as a powerful tool for complex data challenges, but its strengths come with a price tag and learning curve. Carefully evaluating data needs and priorities is crucial before choosing this data integration powerhouse.

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