InfoSphere Information Server vs Skyvia

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Our analysts compared InfoSphere Information Server 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.

Product Basics

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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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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$20,000 Annually
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Product Insights

  • 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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  • 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 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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  • 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

#32

among all
ETL Tools

#33

among all
ETL Tools

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Analyst Rating Summary

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Data Delivery
Metadata Management
Platform Security
Workflow Management
Data Quality
Platform Security

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

InfoSphere Information Server
Skyvia
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Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 100 99 94 95 100 0 100 84 27 65 68 16 79 71 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

Good User Sentiment 80 reviews
Excellent User Sentiment 430 reviews
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.

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)
4.0 (21)
4.8 (220)
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4.8 (67)
4.6 (27)
4.8 (104)
3.1 (32)
4.8 (25)

Awards

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

Workflow Management Award

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

User Favorite Award

Synopsis of User Ratings and Reviews

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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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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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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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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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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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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